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Austria‘s Informative

Inventory Report (IIR) 2020

reduction of national emissions of certain atmospheric pollutants

Transboundary Air Pollution and Directive (EU) 2016/2284 on the

Titel – Erste Zeile … Submission under the UNECE Convention on Long-range

umweltbundesamtu

ENVIRONMENT

AGENCY AUSTRIA

REPORT REP-0723

Vienna 2020

AUSTRIA’S INFORMATIVE INVENTORY REPORT (IIR) 2020

Submission under the UNECE Convention on Long-range Transboundary Air Pollution and Directive (EU) 2016/2284 on the reduction of

national emissions of certain atmospheric pollutants

Since 23 December 2005 the Umweltbundesamt has been accredited as Inspection Body for emission inventories, Type A (ID No. 0241), in accordance with EN ISO/IEC 17020 and the Austrian Accreditation Law (AkkG), by decree of Accreditation Austria (first decree, No. BMWA-92.715/0036-I/12/2005, issued by Accreditation Austria / Federal Ministry of Economics and Labour on 19 January 2006). The information covered refers to the following accreditation scope of the IBE: EMEP 2019 (www.bmdw.gv.at/akkreditierung)

Project management

Michaela Titz

Authors Michael Anderl, Marion Gangl, Simone Haider, Traute Köther, Christoph Lampert, Katja Pazdernik, Daniela Perl, Marion Pinterits, Stephan Poupa, Maria Purzner, Wolfgang Schieder, Günther Schmidt, Barbara Schodl, Michaela Titz, Manuela Wieser, Andreas Zechmeister

Reviewed and approved by

Michael Anderl

Layout and typesetting Elisabeth Riss

Title photograph © Ute Kutschera

The authors of this report want to express their thanks to all experts at the Umweltbundesamt as well as experts from other institutions involved in the preparation of the Austrian Air Emission Inventory for their contribution to the continuous improvement of the inventory.

Reporting entity Contracting entity

Inspektionsstelle Emissionsbilanzen (Inspection Body for Emission Inventories) at the Umweltbundesamt GmbH Spittelauer Lände 5, 1090 Vienna/Austria

BMK - Bundesministerium für Klimaschutz, Um-welt, Energie, Mobilität, Innovation & Technologie (Federal Ministry of Climate Action, Environment, Energy, Mobility, Innovation and Technology) Stubenring 1, 1012 Vienna/Austria

Date of submission

15.03.2020

Responsible for the content of this report

DI Michael Anderl (Head of the inspection body)

Total number of pages

516 Pages

This report is compiled and published as an inspection report in accordance with the Accreditation Law and the in-ternational standard ISO/IEC 17020, in fulfilment of and in compliance with the EMEP/EEA air pollutant emission inventory guidebook (scope of accreditation regarding air pollutants) as well as the Directive (EU) 2016/2284 on the reduction of national emissions of certain atmospheric pollutants (NEC Directive). It replaces the one desig-nated as DRAFT submitted under the UNECE Convention on Long-range Transboundary Air Pollution and Directive (EU) 2016/2284 on March 15th 2020 and has undergone a complete and final quality control and layout/typesetting.

It is an official document, it may not be changed in any form or any means, and no parts may be reproduced or transmitted without prior written permission from the publisher.

For further information about the publications of the Umweltbundesamt please go to: http://www.umweltbundesamt.at/

Imprint

Owner and Editor: Umweltbundesamt GmbH Spittelauer Lände 5, 1090 Vienna/Austria

The Environment Agency Austria prints its publications on climate-friendly paper.

© Umweltbundesamt GmbH, Vienna, 2020 All rights reserved ISBN 978-3-99004-543-5

http://www.umweltbundesamt.at/

Austria’s Informative Inventory Report (IIR) 2020 – Preface

Umweltbundesamt REP-0723, Vienna 2020 3

PREFACE

The report “Austria’s Informative Inventory Report (IIR) 2020” provides a complete and compre-hensive description of the methodologies used for the compilation of the Austrian Air Emission In-ventory (“Österreichische Luftschadstoff-Inventur – OLI”) as presented in Austria’s 2020 submis-sion under the Convention on Long-range Transboundary Air Pollution of the United Nations Economic Commission for Europe (UNECE/LRTAP) and under the Directive (EU) 2016/2284 on the reduction of national emissions of certain atmospheric pollutants (NEC Directive).

Austria is required to annually report data on emissions of air pollutants covered under the UNECE/LRTAP Convention and its Protocols as well as under the NEC Directive for the main pollutants NOx, SO2, NMVOC, NH3 and CO, Particulate Matter (PM), Persistent Organic Pollutants (POPs) and Heavy Metals (HM).

To be able to meet these reporting requirements, Austria compiles an Air Emission Inventory („Österreichische Luftschadstoff-Inventur – OLI”) which is updated annually.

This report follows the regulations under the UNECE/LRTAP Convention and its Protocols that define standards for national emission inventories. In 2008 the Executive Body adopted the Guidelines for Reporting Emission Data under the Convention on Long-Range Transboundary Air Pollution (LRTAP) (ECE/EB.AIR/97)1/2 for estimating and reporting of emission data. They are necessary to ensure transparency, accuracy, consistency, comparability and completeness (TACCC) of the reported emissions. In 2014 the Reporting Guidelines were revised (ECE/EB.AIR.125)3 and were adopted for application in 2015 and subsequent years.

The emission data presented in this report were compiled according to these guidelines for es-timating and reporting emission data, which also define the new format of reporting emission data (Nomenclature for Reporting – NFR (latest version of the templates ‘NFR19’4 dated 18.11.2019) as well as standards for providing supporting documentation which should ensure the transparency of the inventory.

The complete set of tables in the new NFR format, including sectoral reports, sectoral back-ground tables and footnotes to the NFR tables, are submitted separately in digital form only. A summary of emission data is presented in the Appendix of this report.

The IIR 2020 at hand complements the reported emission data by providing background infor-mation. It follows the current template5 of the “Informative Inventory Report – IIR” as elaborated by the LRTAP Convention’s “Task Force on Emission Inventories and Projections – TFEIP” (re-vised in 2018). The structure of this report follows closely the structure of Austria’s National In-ventory Report (NIR) submitted annually under the United Nations Framework Convention on Climate Change (UNFCCC) which includes a complete and comprehensive description of meth-odologies used for compilation of Austria’s greenhouse gas inventory (UMWELTBUNDESAMT 2020a).

1 http://www.ceip.at/fileadmin/inhalte/emep/reporting_2009/Rep_Guidelines_ECE_EB_AIR_97_e.pdf 2 At its twenty-sixth session (15–18 December 2008), the Executive Body approved the revised Guidelines

(ECE/EB.AIR/2008/4) as amended at the session and requested the secretariat to circulate a final amended ver-sion.

3 http://www.ceip.at/fileadmin/inhalte/emep/2014_Guidelines/ece.eb.air.125_ADVANCE_VERSION_ reporting_guidelines_2013.pdf

4 http://www.ceip.at/ms/ceip_home1/ceip_home/reporting_instructions/ 5 Annex II: http://www.ceip.at/ms/ceip_home1/ceip_home/reporting_instructions/annexes_to_guidelines/

http://www.ceip.at/fileadmin/inhalte/emep/reporting_2009/Rep_Guidelines_ECE_EB_AIR_97_e.pdf

http://www.ceip.at/fileadmin/inhalte/emep/2014_Guidelines/ece.eb.air.125_ADVANCE_VERSION_reporting_guidelines_2013.pdf


http://www.ceip.at/ms/ceip_home1/ceip_home/reporting_instructions/

http://www.ceip.at/ms/ceip_home1/ceip_home/reporting_instructions/annexes_to_guidelines/

Austria’s Informative Inventory Report (IIR) 2020 – Preface

4 Umweltbundesamt REP-0723, Vienna 2020

The aim of this report is to document the methodology in order to facilitate understanding of the calculation of the Austrian air emission data. The more interested reader is kindly referred to the background literature cited in this document.

Elisabeth Rigler in her function as head of the Department Climate Change Mitigation & Emis-sion Inventories of the Umweltbundesamt is responsible for the preparation and review of Aus-tria’s Air Emission Inventory as well as for the preparation of the IIR.

Michael Anderl in his function as head of the Inspection Body for Emission Inventories and Katja Pazdernik in her function as deputy are responsible for the content of this report and for the quality management system of the Austrian Air Emission Inventory.

The preparation and review of Austria’s National Air Emission Inventory are the responsibility of the Department “Climate Change Mitigation & Emission Inventories” of the Umweltbundesamt.

Project leader for the preparation of the Austrian Air Emission Inventory is Stephan Poupa.

Specific responsibilities for the preparation of the Austrian Air Emission Inventory are: Data Management ............................................. Stephan Poupa Fuel combustion stationary ............................... Stephan Poupa (‘Sector Lead’) Fuel combustion mobile .................................... Barbara Schodl (‘Sector Lead’) Fugitive emissions ............................................ Marion Pinterits (‘Sector Lead’) Industrial processes .......................................... Michaela Titz (‘Sector Lead’) Solvent Use ....................................................... Maria Purzner (‘Sector Lead’) Agriculture ......................................................... Michael Anderl (‘Sector Lead’) Waste ................................................................ Christoph Lampert (‘Sector Lead’) Key Category Analysis ...................................... Andreas Zechmeister Uncertainty Analysis .......................................... Andreas Zechmeister

Project leader for the preparation of the IIR 2020 are Michaela Titz and Daniela Perl.

Specific responsibilities for the IIR 2020 have been as follows: Executive Summary ....................................... Michaela Titz, Daniela Perl, Marion Gangl Chapter 1 Introduction .................................... Michaela Titz, Günther Schmidt Chapter 2 Trends ........................................... Michaela Titz, Daniela Perl, Marion Gangl Chapter 3 Energy ........................................... Stephan Poupa, Günther Schmidt, Wolfgang

Schieder Chapter 3 Transport ....................................... Barbara Schodl, Günther Schmidt Chapter 3 Fugitive emission ........................... Marion Pinterits, Traute Köther Chapter 4 Industrial Processes and

Product Use………………………………... ..... Maria Purzner, Michaela Titz, Manuela Wieser Chapter 5 Agriculture ..................................... Michael Anderl, Simone Haider Chapter 6 Waste ............................................ Christoph Lampert, Katja Pazdernik Chapter 7 Recalculations & Improvements…. ............................................ Michaela Titz, Daniela Perl Chapter 8 Projections ..................................... Michaela Titz Chapter 9 Reporting of gridded

emissions and LPS ................................... Simone Haider, Günther Schmidt Appendix ........................................................ Michaela Titz, Daniela Perl, Marion Gangl

Austria’s Informative Inventory Report (IIR) 2020 – Content


CONTENT

EXECUTIVE SUMMARY ........................................................................................................ 11 ES.1 Reporting obligations under UNECE/LRTAP and Directive (EU) 2016/2284

(NEC Directive) ............................................................................................................. 11 ES.2 Differences with other reporting obligations ................................................................. 12 ES.3 Overview of emission trends .......................................................................................... 12 ES.4 Key categories .................................................................................................................. 14 ES.5 Main differences in the inventory since the last submission ...................................... 14 ES.6 Improvement Process ...................................................................................................... 15 ES.7 Condensable component of PM10 and PM2.5 .................................................................. 16

1 INTRODUCTION ......................................................................................................... 17 1.1 National inventory background .................................................................................. 17 1.2 Institutional, legal and procedural arrangements .................................................... 18 1.2.1 National Inventory System Austria (NISA) ..................................................................... 21 1.2.2 Austria’s Obligations ...................................................................................................... 23 1.3 Inventory Preparation Process ................................................................................... 27 1.4 Methodologies and Data Sources Used .................................................................... 29 1.4.1 EU Emissions Trading System (EU ETS) ...................................................................... 31 1.4.2 Electronic Data Management (EDM) ............................................................................. 32 1.4.3 Other data (E-PRTR) ..................................................................................................... 33 1.4.4 Literature ........................................................................................................................ 33 1.4.5 Summary of methodologies applied for estimating emissions ....................................... 34 1.5 Key Category Analysis ................................................................................................ 38 1.6 Quality Assurance, Quality Control and verification ................................................ 60 1.6.1 Requirements of the ISO compared to the IPCC 2006 GL as well as the

EMEP/EEA Air Pollutant Emission Inventory Guidebook 2016 ..................................... 60 1.6.2 Quality policy and objectives .......................................................................................... 61 1.6.3 Design of the Austrian QMS .......................................................................................... 63 1.6.4 QA/QC Plan ................................................................................................................... 64 1.6.5 QC Activities ................................................................................................................... 65 1.6.6 QA Activities ................................................................................................................... 65 1.6.7 Error correction and continuous improvement ............................................................... 67 1.6.8 Archiving and documentation ......................................................................................... 67 1.6.9 Treatment of confidentiality issues ................................................................................. 68 1.6.10 QMS activities and improvements 2019 ........................................................................ 68 1.7 Uncertainty Assessment ............................................................................................. 69 1.7.1 Method used .................................................................................................................. 69 1.7.2 Data source .................................................................................................................... 69 1.7.3 Results of uncertainty estimation ................................................................................... 70 1.8 Completeness ............................................................................................................... 89

2 EXPLANATIONS OF KEY TRENDS ....................................................................... 92 2.1 Emission Trends for Air Pollutants covered by the Multi-Effect Protocol

as well as CO ................................................................................................................ 93



2.1.1 SO2 Emissions ............................................................................................................... 94 2.1.2 NOx Emissions ............................................................................................................... 97 2.1.3 NMVOC Emissions ...................................................................................................... 100 2.1.4 NH3 Emissions ............................................................................................................. 104 2.1.5 Carbon monoxide (CO) Emissions .............................................................................. 107 2.2 Emission Trends for Particulate matter (PM) .......................................................... 110 2.3 Emission Trends for Heavy Metals .......................................................................... 120 2.3.1 Cadmium (Cd) Emissions ............................................................................................ 121 2.3.2 Mercury (Hg) Emissions ............................................................................................... 125 2.3.3 Lead (Pb) Emissions .................................................................................................... 128 2.4 Emission Trends for POPs ........................................................................................ 131 2.4.1 Polycyclic Aromatic Hydrocarbons (PAH) Emissions .................................................. 133 2.4.2 Dioxins and Furan (PCDD/F) ....................................................................................... 137 2.4.3 Hexachlorobenzene (HCB) Emissions......................................................................... 140 2.4.4 Polychlorinated biphenyl (PCB) Emissions .................................................................. 143 2.5 National emission total calculated on the basis of fuels used ............................. 146

3 ENERGY (NFR SECTOR 1).................................................................................... 151 3.1 NFR 1.A Stationary Fuel Combustion Activities ..................................................... 151 3.1.1 General description ...................................................................................................... 151 3.1.2 Methodological issues .................................................................................................. 155 3.1.3 NFR 1.A.1 Energy Industries ....................................................................................... 157 3.1.4 NFR 1.A.2 Manufacturing Industry and Combustion ................................................... 175 3.1.5 NFR 1.A.3.e.1 Pipeline compressors ........................................................................... 202 3.1.6 Quality Assurance and Quality Control (QA/QC) ......................................................... 203 3.1.7 Planned improvements ................................................................................................ 204 3.1.8 Recalculations .............................................................................................................. 204 3.1.9 NFR 1.A.4 Other sectors .............................................................................................. 205 3.2 NFR 1.A Mobile Fuel Combustion Activities ........................................................... 243 3.2.1 General description ...................................................................................................... 243 3.2.2 Key Categories ............................................................................................................. 245 3.2.3 Uncertainty Assessment .............................................................................................. 245 3.2.4 NFR 1.A.3.a Civil Aviation – LTO ................................................................................. 246 3.2.5 NFR Memo Item 1.A.3.a Civil Aviation – Cruise .......................................................... 259 3.2.6 NFR 1.A.3.b Road Transport ....................................................................................... 262 3.2.7 Other mobile sources – Off Road ................................................................................ 276 3.2.8 Emission factors for heavy metals, POPs and PM used in NFR 1.A.3

Transport ...................................................................................................................... 291 3.3 NFR 1.B Fugitive Emissions ..................................................................................... 299 3.3.1 Completeness .............................................................................................................. 299 3.3.2 NFR 1.B.1.a Coal mining and handling – Methodological issues ................................ 301 3.3.3 NFR 1.B.2.a Oil – Methodological issues .................................................................... 302 3.3.4 NFR 1.B.2.b Natural Gas – Methodological issues ..................................................... 304 3.3.5 NFR 1.B.2.d Other fugitive emissions from energy production –

Methodological issues .................................................................................................. 305 3.3.6 Category-specific QA/QC ............................................................................................. 306 3.3.7 Uncertainty Assessment .............................................................................................. 306



3.3.8 Category-specific Recalculations ................................................................................. 307 3.3.9 Planned Improvements ................................................................................................ 307

4 INDUSTRIAL PROCESSES AND PRODUCT USE (NFR SECTOR 2) ................................................................................................................ 308

4.1 Sector overview .......................................................................................................... 308 4.1 General description ................................................................................................... 308 4.1.1 Completeness .............................................................................................................. 308 4.1.2 Key Categories ............................................................................................................. 310 4.1.3 Methodology ................................................................................................................. 311 4.1.4 Uncertainty Assessment .............................................................................................. 311 4.1.5 Quality Assurance and Quality Control (QA/QC) ......................................................... 312 4.1.6 Planned Improvements ................................................................................................ 313 4.2 NFR 2.A.1-2.A.3 Mineral Products ............................................................................ 314 4.2.1 Fugitive Particulate Matter emissions .......................................................................... 314 4.2.2 NFR 2.A.5 Mining, Construction/Demolition ................................................................ 316 4.2.3 Category-specific Recalculations ................................................................................. 316 4.3 NFR 2.B Chemical Products ..................................................................................... 317 4.3.1 NFR 2.B.1 Ammonia and 2.B.2 Nitric Acid Production ................................................ 317 4.3.2 NFR 2.B.10 Other Chemical Industry .......................................................................... 319 4.3.3 Category-specific Recalculations ................................................................................. 323 4.4 NFR 2.C Metal Production ......................................................................................... 323 4.4.1 NFR 2.C.1 Iron and Steel Production .......................................................................... 323 4.4.2 NFR 2.C.2 – 2.C.6 Non-ferrous Metals ........................................................................ 329 4.4.3 Category-specific Recalculations ................................................................................. 330 4.5 NFR 2.D.3-2.G Solvents and other Product use ...................................................... 330 4.5.1 Emission Trends .......................................................................................................... 331 4.5.2 NMVOC Emissions from Solvent and other product use (Category 2.D.3.a-i) .............. 333 4.5.3 NFR 2.D.3.b., 2.D.3.c. and 2.D.3. g - NMVOC Emissions related to Asphalt ........ 339 4.5.4 Emissions from Other Product Manufacture and Use (Category 2.G) ........................ 340 4.5.5 Category-specific Recalculations ................................................................................. 342 4.6 NFR 2.H Other processes .......................................................................................... 343 4.6.1 NFR 2.H.2 Food and Beverages Industry .................................................................... 343 4.6.2 Category-specific Recalculations ................................................................................. 344 4.7 NFR 2.I Wood Processing ......................................................................................... 344 4.7.1 Source Category Description ....................................................................................... 344 4.7.2 Methodological Issues ................................................................................................. 344 4.7.3 Category-specific Recalculations ................................................................................. 346

5 AGRICULTURE (NFR SECTOR 3) ....................................................................... 347 5.1 Sector Overview ......................................................................................................... 347 5.2 General description ................................................................................................... 347 5.2.1 Completeness .............................................................................................................. 347 5.2.2 Key Categories ............................................................................................................. 349 5.2.3 Methodology ................................................................................................................. 349 5.2.4 Uncertainty Assessment .............................................................................................. 350 5.2.5 Quality Assurance and Quality Control (QA/QC) ......................................................... 351



5.2.6 Planned Improvements ................................................................................................ 352 5.3 NFR 3.B Manure Management .................................................................................. 352 5.3.1 Methodological Issues ................................................................................................. 352 5.3.2 NH3 emissions from cattle (3.B.1) and swine (3.B.3) ................................................... 357 5.3.3 NH3 emissions from sheep (3.B.2), goats (3.B.4.d), horses (3.B.4.e), poultry

(3.B.4.g) and other animals (3.B.4.h) ........................................................................... 367 5.3.4 NH3 emissions from biogas plants ............................................................................... 369 5.3.5 NOx emissions from Manure Management (3.B) ......................................................... 371 5.3.6 N2 emissions from manure management ..................................................................... 371 5.3.7 NMVOC from Manure Management (3.B) ................................................................... 372 5.3.8 Category-specific Recalculations ................................................................................. 374 5.4 NFR 3.B Particle Emissions from Manure Management ........................................ 375 5.4.1 Methodological Issues ................................................................................................. 375 5.4.2 Category-specific Recalculations ................................................................................. 376 5.5 NFR 3.D Agricultural Soils ........................................................................................ 376 5.5.1 Methodological Issues ................................................................................................. 376 5.5.2 Inorganic N-fertilizers (NFR 3.D.a.1)............................................................................ 377 5.5.3 Organic N-fertilizers applied to soils (NFR 3.D.a.2) ..................................................... 379 5.5.4 Urine and dung deposited by grazing animals (NFR 3.D.a.3) ..................................... 388 5.5.5 Cultivated crops (3.D.e) ............................................................................................... 388 5.5.6 Use of Pesticides (3.D.f) .............................................................................................. 390 5.5.7 Category-specific Recalculations ................................................................................. 391 5.6 NFR 3.D Particle Emissions from Agricultural Soils .............................................. 393 5.6.1 Methodological Issues ................................................................................................. 393 5.6.2 Category-specific Recalculations ................................................................................. 395 5.7 NFR 3.F Field Burning of Agricultural Residues .................................................... 395 5.7.1 Methodological Issues ................................................................................................. 395 5.7.2 Category-specific Recalculations ................................................................................. 397

6 WASTE (NFR SECTOR 5) ...................................................................................... 398 6.1 Sector Overview ......................................................................................................... 398 6.2 General description ................................................................................................... 400 6.2.1 Completeness .............................................................................................................. 400 6.2.2 Key Categories ............................................................................................................. 401 6.2.3 Methodology ................................................................................................................. 401 6.2.4 Uncertainty Assessment .............................................................................................. 401 6.2.5 Quality Assurance and Quality Control (QA/QC) ......................................................... 402 6.2.6 Planned Improvements ................................................................................................ 403 6.3 NFR 5.A Waste Disposal on Land ............................................................................ 403 6.3.1 NMVOC, NH3, CO and heavy metals emissions ......................................................... 403 6.3.2 PM emissions ............................................................................................................... 413 6.4 NFR 5.B Composting ................................................................................................. 414 6.4.1 Source Category Description ....................................................................................... 414 6.4.2 Methodological Issues ................................................................................................. 415 6.4.3 Category-specific Recalculations ................................................................................. 417 6.5 NFR 5.C Incineration and open burning of waste ................................................... 418 6.5.1 Source Description ....................................................................................................... 418



6.5.2 Methodology ................................................................................................................. 418 6.5.3 Category-specific Recalculations ................................................................................. 422 6.6 NFR 5.D Wastewater handling .................................................................................. 422 6.6.1 Source Category Description ....................................................................................... 422 6.6.2 Methodological Issues ................................................................................................. 422 6.6.3 Category-specific Recalculations ................................................................................. 424 6.7 NFR 5.E Other Waste ................................................................................................. 424 6.7.1 Source Category Description ....................................................................................... 424 6.7.2 Methodological Issues ................................................................................................. 425 6.7.3 Category-specific Recalculations ................................................................................. 427

7 RECALCULATIONS AND IMPROVEMENTS ..................................................... 428 7.1 Relation to data reported earlier ............................................................................... 428 7.2 Explanations and Justifications for Recalculations, including in

response to the review process ............................................................................... 428 7.2.1 Energy (1) .................................................................................................................... 429 7.2.2 Industrial Processes and Product Use (2) ................................................................... 431 7.2.3 Agriculture (3) ............................................................................................................... 432 7.2.4 Waste (5) ...................................................................................................................... 435 7.3 Recalculations per Pollutant ..................................................................................... 436 7.4 Planned improvements, including in response to the review process,

and planned improvements to the inventory .......................................................... 441

8 PROJECTIONS ......................................................................................................... 454

9 REPORTING OF GRIDDED EMISSIONS AND LPS .......................................... 456 9.1 Gridded Emissions .................................................................................................... 456 9.1.1 Background Information ............................................................................................... 456 9.1.2 Emissions according to the GNFR-Code ..................................................................... 456 9.1.3 Allocation of emissions ................................................................................................ 457 9.1.4 Results of gridded data ................................................................................................ 461 9.2 Large Point Sources (LPS) ........................................................................................ 465 9.2.1 Activity Data ................................................................................................................. 465 9.2.2 Methodological Issues ................................................................................................. 466 9.3 Recalculations ............................................................................................................ 466 9.4 Planned Improvements ............................................................................................. 466

10 REFERENCES .......................................................................................................... 467

11 ABBREVIATIONS .................................................................................................... 488

12 APPENDIX ................................................................................................................. 491 12.1 Emission Trends per Sector – Submission under UNECE/LRTAP ....................... 491 12.2 National emission total for SO2, NOx, NMVOC and NH3 calculated on the

basis of fuels used ..................................................................................................... 506 12.3 Information on PM emission factors (include/exclude the condensable

component) ................................................................................................................. 511

Austria’s Informative Inventory Report (IIR) 2020 – Executive Summary


EXECUTIVE SUMMARY

ES.1 Reporting obligations under UNECE/LRTAP and Directive (EU) 2016/2284 (NEC Directive)

Austria’s Informative Inventory Report (IIR) and the complete set of NFR tables (the latter are submitted in digital format only) represent Austria’s official submission under the United Nations Economic Commission for Europe (UNECE) Convention on Long-rage Transboundary Air Pollu-tion (LRTAP) and under Directive (EU) 2016/2284 (NEC Directive). The Umweltbundesamt in its role as single national entity regarding emission inventories compiles Austria’s annual delivery, and the Austrian Federal Ministry of ‘Climate Action, Environment, Energy, Mobility, Innovation and Technology’ (BMK) submits it officially to the Executive Secretary of UNECE as well as to the European Commission.

As a party to the UNECE/LRTAP Convention and under the NEC Directive, Austria is required to annually report data on emissions of air pollutants covered in the Convention and its Proto-cols: main pollutants: nitrogen oxides (NOx), non-methane volatile organic compounds (NMVOC),

sulphur oxides (SOx), ammonia (NH3) and carbon monoxide (CO); particulate matter (PM): primary PM (fine particulate matter (PM2.5) and coarse particulate

matter (PM10)6; priority heavy metals (HMs): lead (Pb), cadmium (Cd) and mercury (Hg); persistent organic pollutants (POPs): polychlorinated dibenzodioxins/dibenzofurans (PCDD/Fs),

polycyclic aromatic hydrocarbons (PAHs), hexachlorobenzene (HCB) and polychlorinated bi-phenyls (PCBs).

In order to fulfil these reporting requirements, Austria compiles an Air Emission Inventory (“Österreichische Luftschadstoff-Inventur – OLI”), which is updated annually. The IIR contains information on Austria’s inventories of air pollutants for all years from 1990 to 2018 for the main pollutants, for POPs and HMs and for the years 1990, 1995 and from 2000 onwards for PM.

From submission 2020 onwards, Austria reports all pollutants in the NFR19 reporting format from 1990 to the latest inventory year. Emissions of the years before 1990 were last updated and published in submission 2014.7

In addition, the report includes both detailed descriptions of methods, data sources and uncer-tainties and information on quality assurance and quality control (QA/QC) activities as well as analyses of emission trends.

The emission data presented in this report were compiled according to the revised 2014 Report-ing Guidelines (ECE/EB.AIR.125) that were approved by the Executive Body for the UNECE/LRTAP Convention at its 36th session.

The Austrian inventory is complete with regard to reported gases, reported years and reported emissions from all sources, and also complete in terms of geographic coverage.

6 According to the CLRTAP Reporting GL the reporting of total suspended particules (TSPs) is not mandatory, but re-

ported by Austria. 7 Austria´s submission 2014 under the Convention on Long-range Transboundary Air Pollution covering the years

1980–2012: http://www.ceip.at/ms/ceip_home1/ceip_home/status_reporting/2014_submissions/

http://www.ceip.at/ms/ceip_home1/ceip_home/status_reporting/2014_submissions/



ES.2 Differences with other reporting obligations

NEC Directive (EU) 2016/2284 sets out national emission reduction commitments for the pollu-tants SO2, NOx, VOC, NH3 and PM2.5. Austria uses the national emission totals calculated on the basis of fuel used (thus excluding emissions from fuel exports in the vehicle tank) for compli-ance assessment under the NEC Directive.

The annual greenhouse gas reporting under the UNFCCC and the Kyoto Protocoll also requires the reporting of indirect GHGs (NOx, CO, NMVOC) and SO2 emissions based on fuel sold. In contrast to UNFCCC requirements, emissions from aviation under the NEC Directive and the LRTAP Convention include domestic LTO and cruise. Furthermore, international navigation of inland waterways is covered under NEC and CLRTAP.

ES.3 Overview of emission trends

Main Pollutants

In 1990, national total SO2 emissions amounted to 74 kt. Since then emissions have decreased quite steadily. In the year 2018, emissions were reduced by 84.0% compared to 1990 and amounted to 12 kt. This decline is mainly caused by a reduction of the sulphur content in miner-al oil products and fuels (according to the Austrian Fuel Ordinance), the installation of desul-phurisation units in plants (according to the Clean Air Act for boilers) and an increased use of low-sulphur fuels like natural gas. The economic crisis in 2009 caused a decrease in emis-sions, followed by an increase due to the recovery of the economy. The strong reduction in emissions between 1991 and 1992 can be explained by reduced coal consumption in power plants (1.A.1.a) and a reduction of SO2 emissions from oil fired power plants (1.A.1.a) as well as from iron and steel (1.A.2.a) and pulp and paper (1.A.2.d) production. From 2017 to 2018 emis-sions decreased by 8.4%. This was mainly caused by reductions in emissions from iron and steel (1.A.2.a).

In 1990, national total NOx emissions amounted to 217 kt. After an all-time high of emissions be-tween 2003 and 2005 emissions are decreasing continuously. This is mainly due to reduced emissions from heavy trucks, especially because of improvements in the after treatment tech-nology. In 2018, NOx emissions amounted to 151 kt and were about 31% lower than in 1990. From 2017 to 2018 emissions decreased by 6.8%. This was caused by the decline in road traf-fic, especially of heavy duty vehicles and passenger cars. In 2018 53% of the total nitrogen ox-ides emissions originate from road transport (including fuel exports). Austria is a landlocked country and fuel prices significantly vary between neighbouring countries. So Austria has expe-rienced a considerable amount of ‘fuel export’ and the share of NOx emissions caused by fuel sold in Austria but used abroad is notable. Emissions for 2018 based on fuel used amount to 136 kt and are about 15 kt lower than based on fuel sold; the decrease between 1990 and 2018 is slightly stronger (-32%).

In 1990, national total NMVOC emissions amounted to 334 kt. Emissions have decreased steadily since then and in the year 2018 emissions were reduced by 68% to 107 kt compared to 1990. The largest reductions were achieved in the road transport sector due to an increased use of catalytic converters and diesel cars. Reductions in the solvent sector were due to several regulations (Solvent Ordinance, Cogeneration Act, VOC Emissions Ordinance). From 2017 to 2018 emissions decreased by 3.2%.

In 1990, national total NH3 emissions amounted to 62 kt; emissions have increased over the pe-riod from 1990 to 2018. In 2018, emissions were 4.7% above 1990 levels and amounted to 65 kt. NH3 in Austria is almost exclusively emitted in the agricultural sector. The higher NH3 emis-



sions (in spite of a decrease in the number of cattle) can be explained by an increase in loose housing systems (to ensure animal welfare and according to EU law) and an increase of high-capacity dairy cows. Additionally, there has been an increase in the use of urea as nitrogen ferti-liser (a cost-efficient but otherwise less efficient fertiliser). Compared to the previous year, emis-sions in 2018 decreased by 1.6%. The main reason is the lower amount of mineral fertilizer, in particular urea, which was applied on agricultural soils. Furthermore, the livestock numbers of cattle (dairy cows and other cattle) and swine were falling. However, increased N excretion due to increased milk yields counterbalanced the decreasing dairy cow number.

In 1990, national total CO emissions amounted to 1 249 kt. Emissions considerably decreased from 1990 to 2018. In 2018, emissions were 61% below 1990 levels and amounted to 490 kt. This reduction was mainly due to decreasing emissions from road transport (catalytic converters). The emissions decreased between 2017 and 2018 by 7.4%, mainly due to sectors iron and steel and residential (stationary).

Particulate Matter Particulate matter emissions in Austria mainly arise from industrial processes, road transport, agriculture and small heating installations.

Particulate matter (PM) emissions show a decreasing trend over the period 1990 to 2018: TSP emissions decreased by 28%, PM10 emissions were about 35% below the level of 1990, and PM2.5 emissions dropped by about 48%. Between 2017 and 2018 PM10, PM2.5 and TSP emissions de-creased by 4.3% (PM10), 6.8% (PM2.5) and 3.4% (TSP). The decrease of TSP, PM10 and PM2.5

was mainly because of reductions in the sector 1 A 4 b 1 residential: stationary, due to the mild weather in 2018 and a decrease in the use of biomass for heating. To a small extent, the latest decline can also be explained by efficiency improvements through thermal renovation and by a switch to modern biomass boilers and stoves (improvements in fuel combustion technologies). TSP emissions also decreased slightly due to reduced emissions from 2.A.5.a Quarrying and min-ing of minerals other than coal.

Heavy Metals Emissions of all three priority heavy metals (Cd, Pb and Hg) have decreased since 1990.

The overall Cd emissions reduction of 35% from 1990 to 2018 is mainly due to a decline in the in-dustrial processes and energy sector, which is due to reduced use of heavy fuel oil and lower process emissions from iron and steel production. In the last years emissions remained quite sta-ble, the increased emission level 2017 was due to higher emissions from iron and steel production and from industrial processes.

The overall reduction of Hg of about 56% for the period 1990 to 2018 was due to decreasing emis-sions from cement industries and the industrial processes sector as well as due to reduced use of coal for residential heating. Several bans in different industrial sub-sectors and in the agricul-ture sector led to the sharp fall of total Hg emission in Austria by the year 2000. Between 2017 and 2018 emissions decreased by 7.0% mainly because of reduced emissions from NFR 2.C.1 Iron and Steel Production.

The overall reduction trend of Pb emissions was minus 92% for the period 1990 to 2018, which is mainly a result of the ban of lead in gasoline. However, abatement techniques and product substi-tutions also contributed to the emission reduction. Compared to the previous year Pb emissions show a decrease of 6.2% as a result of reduced emissions from Iron and Steel Production (2.C.1).

http://dict.leo.org/ende?lp=ende&p=/gQPU.&search=particulate

http://dict.leo.org/ende?lp=ende&p=/gQPU.&search=matter



Persistent Organic Pollutants (POPs) Emissions of all POPs decreased remarkably from 1990 to 2018 (HCB -58%, PAH -64%, PCDD/F -73% and PCBs -32%), where the highest achievement was made until 1995. The sig-nificant increase of HCB emissions in the years 2012, 2013 and 2014 was due to unintentional releases of HCB by an Austrian cement plant.

In 2018 PCB emissions decreased by 16% compared to the previous year 2017, due to reduced emissions from sector 2.C.1 Iron and Steel Production. PCDD/F emissions decreased by 7.5% compared to the previous year 2017, PAH emissions decreased by 8.1% and HCB emissions by 9.6% in the same time. These reductions are mainly due to the warm weather and thus reduced emissions from residential heating (decreased bio-mass consumption) as well as due to a decrease of iron and steel production (2.C.1) (relevant for HCB and PCDD/F). Dioxin/furan emissions from sector Waste (5.E Other Waste) also de-creased remarkably from 2017 to 2018, although the share of this category in national total emissions is only 6%.

The most important source for PAH, PCDD/F and HCB emissions in Austria is residential heat-ing. In the 80s industry and waste incineration were still important sources regarding POP emis-sions. Due to legal regulations concerning air quality emissions from industry and waste incin-eration decreased remarkably from 1990 to 1993. For PCB emissions the most important source category is 2.C Metal Production.

ES.4 Key categories

To determine key categories, a trend and a level assessment have been carried out, which re-sulted in 43 identified key categories. It shows that the residential sector has been identified as the most important key category: all air pollutants except for NH3 and PCB are found key in ei-ther the trend or the level assessment. In the following table the top 5 ranked key categories are listed.

Table 1: Most relevant key categories in Austria for air emissions 2018.

Name of key category No of occurrences as key category 1.A.4.b.1 – Residential: stationary 26 times (SO2, NOx, NMVOC, CO, Cd, Pb, Hg, PAH,

DIOX, HCB, TSP, PM10, PM2.5) 1.A.1.a – Public Electricity and Heat Production

18 times (SO2, NOx, NMVOC, CO, Cd, Pb, Hg, DIOX, TSP, PM10, PM2.5)

2.C.1 – Iron and Steel Production 14 times (Cd, Pb, Hg, DIOX, HCB, PCB, PM10) 1.A.3.b – 1 R.T., Passenger cars 12 times (NOx, NMVOC, CO, TSP, PM10, PM2.5) 1.A.2.d – Pulp, Paper and Print 8 times (SO2, Cd, Pb, Hg)

ES.5 Main differences in the inventory since the last submission

As a result of the continuous improvement process of Austria’s Annual Air Emission Inventory, emissions for some sources have been recalculated, e.g. on the basis of updated activity data or revised methodologies. Thus emission data for the whole time series submitted this year dif-fer from the data reported previously.



In NFR sector 1 Energy, changes are mainly due to revisions of the energy balance. Natural gas gross inland consumption 2014 and 2015 has been revised downwards. However, natural gas consumption has been shifted to different sectors. For liquid fuels, gross inland consumption has been revised downwards for the years 2005 to 2011 (crude oil input into refineries) and for the year 2017, which does not have an effect on final consumption, because lower fuel imports have been counterbalanced by higher refinery fuel output. For the period 2013 to 2017, liquid fuels have been shifted from the industry sector (mostly from 1A2e food processing and 1A2g other manufacturing industries) to the residential (1A4b) and commercial (1A4a) sector. For sol-id fuels, mainly the residential sector has been revised for the years since 2005. For ‘biomass’, gross inland consumption has been revised upwards for the whole time series 2005–2017. For the years 2005 to 2016, transformation input to the power sector (1A1a) has been revised downwards while for 2017 it has been revised upwards, which explains most of the higher NOx (+7%) and PM2.5 (+6%) emissions in 2017 of category 1A1a. The largest revision to biomass consumption took place in the 1A4 stationary combustion sub-categories.

In NFR sector 1.A.3 Transport, the domestic activity data (fuel consumption/mileage) has been updated fundamentally with new specific mileage per vehicle category: for the first time, data from periodic roadworthiness testing has been evaluated resulting in new age-related mileage data and improved data accuracy. This affects the categories passenger cars (PC), light-duty vehicles (LDV) and motorcycles (MC). Furthermore, the new HBEFA Version 4.1 was imple-mented, which resulted in increased emission factors for all vehicle categories.

In NFR sector 2 Industrial Processes and Product Use recalculations have been carried out main-ly in subcategory Solvent Use (2.D.3): Following in-depth QC activities, time series inconsisten-cies in the solvents model were removed and has led to a decrease in activity data (Solvents Used), leading to a decrease in emissions. In the categories Iron and Steel Production (2.C.1) and Other processes (2.H.2) estimates for the PAH fractions BAP, BBF, BKF, IND has been included.

More detailed statistical data became available on cigarettes sold in Austria, as well as loose tobacco and cigars, and was used for a review of the timeline.

Due to recalculations of the energy balances, the activity data in category Wood processing (2.I) had to be updated. Thus, particular matter emissions since 2005 have changed.

The main reason for revised emissions in NFR sector 3 Agriculture is the implementation of the new EMEP/EEA Guidebook 2019 in category Manure Management (3.B). For mineral fertiliser application, rapid incorporation of urea into agricultural soils was considered for the first time. Inventory improvements resulted in lower NH3 emissions over the whole time series.

In NFR sector 5 Waste, the main revisions werde made in category Wastewater (5.D): For NMVOC from category 5.D.1 domestic wastewater a recalculation for 2017 was carried out as new data on wastewater volumes became available. This new data was used to replace activity data that had been extrapolated based on population growth.

For more detailed information see Chapter 7 – Recalculations and Improvements.

ES.6 Improvement Process

The Austrian Air Emission Inventory is subject to a continuous improvement programme result-ing in annual recalculations (see Chapter ES.5 above). Furthermore, the regularly conducted reviews under the LRTAP Convention and the NEC Directive trigger improvements.



The last CLRTAP Stage 3 (“In-depth”) review of the Austrian Inventory took place in 2017 (UNITED NATIONS 2017). The findings for Austria are summarized and commented in Table 319. The next Stage 3 review is currently not scheduled, but will be within the next five years.

In addition to the CLRTAP Review, from 2017 onwards the national emission inventory data is also checked by the European Commission as set out in Article 10 of Directive 2016/2284. The inventories are checked annually in order to verify the transparency, accuracy, consistency, comparability and completeness of information submitted and to identify possible inconsisten-cies with the requirements set out under international law, in particular under the LRTAP Con-vention. Synergies are maximised with the 'Stage 3' reviews conducted by the LRTAP Conven-tion. The findings under the NEC Review 2018 for Austria are summarized and commented in Table 320.

Recalculations and improvements are summarized in Chapter 7 – Recalculations and Improve-ments and described in detail in the sector-specific chapters of this report.

ES.7 Condensable component of PM10 and PM2.5

The Parties to the LRTAP Convention have been formally requested by the Executive Body at its thirty-eight session to provide information on the reporting of the condensable component of particulate matter (PM) in their Informative Inventory Reports. The purpose is the provision of transparent information for the modellers. As a consequence, Annex II (Recommended struc-ture for the Informative Inventory Report (IIR)) of the CLRTAP Reporting GL has been updated accordingly. Austria included the following information in its IIR from 2019 on: appendix including a table summarising whether PM10 and PM2.5 emission factors for each

source sector include or exclude the condensable component (and references for their emis-sion factors) (see chapter 12.3).

indication in the methodology sections whether PM10 and PM2.5 emission estimates include or exclude the condensable component (please refer to the methodological chapters 3-6).

Austria’s Informative Inventory Report (IIR) 2020 – Introduction


1 INTRODUCTION

1.1 National inventory background

The Federal Ministry of Climate Action, Environment, Energy, Mobility, Innovation and Technol-ogy (BMK) administrates Austria’s reporting obligations to the Convention on Long-range Transboundary Air Pollution (LRTAP)8 of the United Nations Eco-

nomic Commission for Europe (UNECE),9 United Nations Framework Convention on Climate Change (UNFCCC),10 European Commission (EC),11 and the European Environment Agency (EEA).12

The Environmental Control Act (Umweltkontrollgesetz, UKG)13 that entered into force on the 1st of January 1999 regulates responsibilities of environmental control in Austria and lists the tasks of the Umweltbundesamt. The Umweltbundesamt is designated as single national entity with overall responsibility for inventory preparation.

Furthermore, the Environmental Control Act incorporates the Umweltbundesamt as a private lim-ited company. To ensure that the Umweltbundesamt has the resources required to fulfil all listed tasks, the financing is set up as a fixed amount of money annually allocated to the Umweltbun-desamt. The Umweltbundesamt is free to manage this so called “basic funding”, provided that the tasks are fulfilled. Projects beyond the scope of the Environmental Control Act are financed on project basis by the contracting entity, which may be national or EC authorities as well as private entities.

One task is the preparation of technical expertise and the data basis for fulfilment of the obliga-tions under the UNFCCC, UNECE and EC. Thus the Umweltbundesamt prepares and annually updates the Austrian Air Emissions Inventory (“Österreichische Luftschadstoff-Inventur OLI”), which covers greenhouse gases and emissions of other air pollutants as stipulated in the report-ing obligations further explained in Chapter 1.2.2.

For the Umweltbundesamt, a national air emission inventory that identifies and quantifies the sources of pollutants in a consistent manner is of a high priority. Such an inventory provides a common means for comparing the relative contribution of different emission sources and hence can serve as an important basis for policies to reduce emissions.

8 https://www.unece.org/env/lrtap/welcome.html 9 http://www.unece.org 10 http://unfccc.int/2860.php 11 http://ec.europa.eu/index_en.htm 12 http://www.eea.europa.eu/ 13 „Umweltkontrollgesetz” – Bundesgesetz über die Umweltkontrolle und die Einrichtung einer Umweltbundesamt Gesell-

schaft mit beschränkter Haftung; Federal Law Gazette I 152/1998

https://www.unece.org/env/lrtap/welcome.html

http://www.unece.org/

http://unfccc.int/2860.php

http://ec.europa.eu/index_en.htm

http://www.eea.europa.eu/

http://ta1.umweltbundesamt.at/fileadmin/site/umweltkontrolle/gesetze/ukg.pdf



1.2 Institutional, legal and procedural arrangements

The Umweltbundesamt established an Inspection Body for Emission Inventories (IBE, hereinaf-ter also referred to as inspection body) which is entrusted with the preparation of emission in-ventories as assigned to the Umweltbundesamt as described above (refer to Chapter 1.1). So, since 23 December 2005, the Umweltbundesamt has been accredited as Inspection Body for Emission Inventories, Type A (Id.No. 0241), in accordance with EN ISO/IEC 17020 and the Austrian Accreditation Law (AkkG),14 by decree of Accreditation Austria (first decree, No. BMWA-92.715/0036-I/12/2005, issued by Accreditation Austria / Federal Ministry of Economics and Labour on 19 January 2006). The accreditation comprises the emission inventory for all GHGs and air pollutants as reported under the UNFCCC and the Kyoto Protocol, the EC Monitoring Mechanism as well as the UNECE and NEC Directive (see Chapter 1.6). The personnel of the IBE are made up of staff from various organisational units of the Umwelt-bundesamt, who in the course of their inspection activity are assigned to the IBE and therefore responsible to the head of the inspection body. They are free from any commericial, financial and other pressures that might influence their technical judgement. No technical instructions from outside the IBE are given for the preparation of emission inventories (see Figure 1).

Responsibilities within the Austrian National Inventory System

Figure 1: Responsibilities within the Austrian National Inventory System (Air Pollutants).

14 Federal Law Gazette I No 28/2012 (Akkreditierungsgesetz 2012)

Source: Umweltbundesamt



The quality system is maintained and updated under the responsibility of a quality representa-tive; the inventory work is coordinated by a project manager. For these functions as well as for the head of inspection body deputies are appointed. Regarding the inventory work, specific re-sponsibilities for the different emission source/sink categories (‘Sector Experts’) are defined. There are 8 sectors defined (Energy, Transport, Fugitive Emissions, Industrial Processes, Prod-uct Use, Agriculture, LULUCF15 and Waste). Two experts form a sector team and one of them is nominated as team leader (‘Sector Lead’). For more information on the QMS please refer to Chapter 1.6.

In addition, the Austrian emissions trading registry is managed by the Umweltbundesamt on be-half of the Federal Ministry ‘Climate Action, Environment, Energy, Mobility, Innovation and Tech-nology’ (BMK). This mandate was given to the Umweltbundesamt in the Registry Ordinance (Registerstellenverordnung) Federal Law Gazette II no. 208/2012. Umweltbundesamt is respon-sible for the operational management of the registry and serves as a contact point for national and international authorities.

The Austrian emissions trading registry has been operational since 2005 and serves both as registry for the EU Emissions Trading scheme and as the national registry for Austria as a party of the Kyoto Protocol.

Besides the Environmental Control Act there are some other legal and institutional arrange-ments in place as the main basis for the national system: The Austrian Emissions Certificate Trading Act16 regulates monitoring and reporting in the

context of the EU Emissions Trading scheme (ETS) in Austria. The Umweltbundesamt takes the emission reports of the emissions trading scheme into ac-

count for the national greenhouse gas inventory in order to comply with requirements of the EU Monitoring Mechanism and the UNFCCC. This is not only important for emissions from combustion of fuels, for which more detailed information is availaible in the ETS reports than is provided in the national energy balance, but also for emissions from industrial processes. First data from the EU ETS were available for the year 2005; since then ETS data have been considered in the submissions.

The Austrian statistical office (Statistik Austria) is required by contract with the Federal Minis-try ‘Climate Action, Environment, Energy, Mobility, Innovation and Technology’ (BMK) and with the Federal Ministry for Digital and Economic Affairs (BMDW) to annually prepare the national energy balance (the contracts also cover some quality aspects). The energy balance is prepared in line with the methodology of the Organisation for Economic Co-operation and Development (OECD) and is submitted annually to the International Energy Agency (IEA) (IEA/EUROSTAT Joint Questionnaire (JQ) Submission). The national energy balance is the most important data basis for the Austrian Air Emissions Inventory.

According to national legislation (Bundesstatistikgesetz 200017), the Austrian statistical office has to prepare annual import/export statistics, production statistics and statistics on agricul-tural issues (livestock counts etc.), providing an important data basis for calculating emis-sions from the sectors Industrial Processes, Product Use and Agriculture.

In order to comply with the reporting obligations, the Umweltbundesamt has the possibility to obtain confidential data from the national statistical institute (of course these data have to be treated confidentially). The legal basis for this data exchange is the ‘Bundesstatistikgesetz 2000’17 (federal statistics law), which allows the national statistical office to provide confiden-tial data to authorities that have a legal obligation for the processing of these data.

15 Only relevant for GHG emissions 16 „Emissionszertifikate-Gesetz”; Federal Law Gazette I No. 46/2004 17 „Bundesstatistikgesetz 2000”; Federal Law Gazette I No 163/1999, last amended by Federal Law Gazette I

No 32/2018



According to paragraph 38 (1) of the EG-K 201318 each licensee of an operating boiler with a thermal capacity of more than two megawatts (MW) is obliged to report the emissions to the competent authority. The Umweltbundesamt can request copies of these emission declara-tions. These data are used to verify the data from the national energy balance for the Energy sector.

According to the old Landfill Ordinance (Deponieverordnung 1996)19 the operators of landfill sites had to report type and amount of waste deposited annually. These reports (collected in a central database run by Umweltbundesamt) still provide the main basis for calculating emissions from the sector Waste for the inventory years 1998–2007.

Starting with the deposited waste of the year 2008 landfill operators are – pursuant to the new Landfill Ordinance (Deponieverordnung 2008)20 – obliged to submit their data annually and electronically via the portal http://edm.gv.at (Electronic Data Management – ‘EDM’). Respon-sible for data collection and analysis is the BMK. The necessary data is requested by the Umweltbundesamt for the purpose of inventory preparation.

Since 2004 there is a reporting obligation to the BMK under the Austrian Fluorinated Com-pounds (FC) Ordinance21 for users of FCs for the following applications: refrigeration and air-conditioning, foam blowing, semiconductor manufacture, electrical equipment, fire extin-guishers and aerosols. These data are notified via EDM and used for estimating emissions from the consumption of fluorinated compounds (IPCC sector 2.F).

More information on the National Inventory System in Austria (NISA) is provided in the following Chapter 1.2.1.

18 „Emissionsschutzgesetz für Kesselanlagen 2013“; Federal Law Gazette I No 127/2013 19 „Deponieverordnung“; Federal Law Gazette No 164/1996 20 „Deponieverordnung 2008“; Federal Law Gazette II No 39/2008 21 „Industriegas-Verordnung (HFKW-FKW-SF6-VO)“; Federal Law Gazette II No. 447/2002

http://edm.gv.at/



1.2.1 National Inventory System Austria (NISA)

History of the National Inventory System Austria – NISA

Austria’s National Inventory System (NISA) has to be adapted to different obligations which are subject to continuous development. A brief history of the development and the activities of NISA are provided below:

Austria established estimates for SO2 under EMEP in 1978 (Cooperative Programme for Monitoring and Evaluation of the Long-range Transmission of Air Pollutants in Europe).22

As an EFTA23 country, Austria participated in CORINAIR 90,24/25 an air emission inventory for Europe. It was part of the CORINE (Coordination d’Information Environmentale) work plan set up by the European Council of Ministers in 1985. The aim of CORINAIR 90 was to pro-duce a complete, consistent and transparent emission inventory for the following pollutants: SOx as SO2, NOx as NO2, NMVOC, CH4, CO, CO2, N2O and NH3.

Austria signed the UNFCCC on June 8, 1992 and subsequently submitted its instrument of ratification on February 28, 1994.26 The Convention i.a. includes the commitment to prepare an emission inventory for GHG on a regular basis.

In 1994, the first so-called Austrian Air Emission Inventory (Österreichische Luftschadstoff-Inventur, OLI) was prepared.

In 1997, a consistent time series for the emission data from 1980 to 1995 was reported for the first time.

In 1998, also emissions of heavy metals (HM), persistent organic pollutants (POP) and fluori-nated compounds (FC) were included in the inventory.

Austria signed the KYOTO PROTOCOL on April 4, 1998 and subsequently submitted its in-strument of ratification on May 31, 2002.

Inventory data for particulate matter (PM) were included in the inventory in 2001. The accreditation as Inspection Body for Emission Inventories according to ISO/IEC 17020

was awarded in 2005 and was renewed in 2011 and 2015. For more details on NISA, see the report “NISA – NATIONAL INVENTORY SYSTEM AUSTRIA – Implementation Report”27 which presents an overview of NISA and evaluates its compliance with the guidelines for national systems under Article 5, paragraph 1, of the Kyoto Protocol as specified under the Marrakesh Accord (decision 20/CP.7).28 Organisation of the National Inventory System Austria – NISA

Regulations under the UNECE/LRTAP Convention and its Protocols define and continuously improve standards for the preparation of and reporting on national emission inventories. In 2002, the Executive Body adopted new guidelines for estimating and reporting emission data to en-sure that the transparency, consistency, comparability, completeness and accuracy of reported emissions are adequate for current LRTAP Conventions needs (EB.AIR/GE.1/2002/729 and its supporting addendum). 22 http://www.emep.int/ 23 EFTA: European Free Trade Association; http://www.efta.int/ 24 The CORINAIR system has been integrated into the work programme of the European Environment Agency (EEA)

and the work is continuing through the Agency’s European Topic Centre on Air Emissions (ETC/ACC). 25 http://www.eea.europa.eu/publications/topic_report_1996_21 26 http://unfccc.int/essential_background/convention/status_of_ratification/items/2631.php 27 http://www.umweltbundesamt.at/fileadmin/site/publikationen/REP0004.pdf 28 http://unfccc.int/resource/docs/cop7/13a03.pdf#page=2 29 http://www.unece.org/fileadmin/DAM/env/documents/2002/eb/ge1/eb.air.ge.1.2002.7.e.pdf

http://www.emep.int/

http://www.efta.int/

http://www.eea.europa.eu/publications/topic_report_1996_21

http://unfccc.int/essential_background/convention/status_of_ratification/items/2631.php

http://www.umweltbundesamt.at/fileadmin/site/publikationen/REP0004.pdf

http://unfccc.int/resource/docs/cop7/13a03.pdf#page=2

http://www.unece.org/fileadmin/DAM/env/documents/2002/eb/ge1/eb.air.ge.1.2002.7.e.pdf



The submission is in accordance with the revised Guidelines for Reporting Emission Data under the Convention on Long-range Transboundary Air Pollution (ECE/EB:AIR/125).

As illustrated in Figure 2, the Austrian Air Emission Inventory (OLI), comprising all air pollutants stipulated by various national and international obligations, represents the core of NISA. The nation-al system as required under the Kyoto Protocol and the Quality Management System (ISO/IEC 17020) are incorporated into NISA as complementary sections.

The Austrian Air Emission Inventory (OLI) covers all pollutants, i.e. air pollutants reported to UNECE/EC and greenhouse gases (GHG) as reported to the UNFCCC. This is to streamline ef-forts and benefit from a common approach to inventory preparation in one single National In-ventory System for Austria (NISA).

It is designed to comply with the – generally more stringent – standards for national emission inventories under the UNFCCC and the Kyoto Protocol and also meets all the requirements of the LRTAP Convention and other reporting obligations as presented in Chapter 1.2.2.1.

The “National Inventory System Austria” (NISA) includes all institutional, legal and procedural arrangements made for the preparation of emission inventories and for reporting and archiving inventory information. It should ensure the quality of the inventory: timeliness, transparency, ac-curacy, consistency, comparability, and completeness (TACCC).

As there are many different obligations which are subject to continuous development, Austria’s National Inventory System (NISA) has to be adapted continually to these changes. The present structure is illustrated in Figure 2.

Structure of the National Emission Inventory System Austria (NISA)

Figure 2: Structure of the National Emission Inventory System Austria (NISA).



1.2.2 Austria’s Obligations

Austria has to comply with the following air emission related obligations: UNECE Convention on Long-range Transboundary Air Pollution (LRTAP) and its Protocols

comprising the annual reporting of national emission data on SO2, NOx, NMVOCs, NH3, CO, TSP, PM10, and PM2.5 as well as on the heavy metals Pb, Cd and Hg and persistent organic hydrocarbons (PAHs), dioxins and furans (PCDD/F), hexachlorobenzene (HCB) and Poly-chlorinated biphenyls (PCBs). Austria signed the convention in 1979; since its entry into force in 1983, the Convention has been extended by eight protocols which identify specific obliga-tions or measures to be taken by Parties. These obligations as well as information regarding the status of ratification are listed in Table 2.

Directive (EU) 2016/228430 on the reduction of national emissions of certain atmospheric pol-lutants (NEC-Directive) of the European Parliament and of the Council of 14.12.2016, amend-ing Directive 2003/35/EC and repealing Directive 2001/81/EC. The national air emission ceil-ings law31 transposes the NEC Directive into Austrian national legislation.

„United Nations Framework Convention on Climate Change” (UNFCCC) (1992)32 and the Kyoto Protocol (1997).33

European Council Decision 525/2013/EC34 “Monitoring Mechanism Regulation” on a mecha-nism for monitoring and reporting greenhouse gas emissions and for reporting other infor-mation at national and Union level relevant to climate change.

Austrian “ambient air quality act”35 comprising the reporting of national emission data on SO2, NOx, NMVOC, CO, heavy metals (Pb, Cd, Hg), benzene and particulate matter (PM).

Industrial Emissions Directive 2010/75/EU36 which requires the reporting of air emissions from various industrial activities.

E-PRTR Regulation (EC) No 166/200637 concerning the establishment of a European Pollu-tant Release and Transfer Register. E-PRTR is associated with Article 6 of the Aarhus Con-vention (United Nations: Aarhus, 1998) which refers to the right of the public to access envi-ronmental information and to participate in the decision-making process on environmental is-sues.

30 http://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32016L2284&from=EN 31 Emissionshöchstmengengesetz-Luft EG-L (air emissions ceilings law)

https://www.ris.bka.gv.at/GeltendeFassung.wxe?Abfrage=Bundesnormen&Gesetzesnummer=20002763 32 http://unfccc.int/essential_background/convention/status_of_ratification/items/2631.php 33 http://unfccc.int/files/essential_background/kyoto_protocol/application/pdf/kpstats.pdf 34 http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2013:165:0013:0040:EN:PDF

(repealing Decision 280/2004/EC) 35 Immissionsschutzgesetz-Luft IG-L (ambient air quality law)

https://www.ris.bka.gv.at/GeltendeFassung.wxe?Abfrage=Bundesnormen&Gesetzesnummer=10011027 36 http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2010:334:0017:0119:en:PDF 37 http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2006:033:0001:0017:EN:PDF

http://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32016L2284&from=EN

https://www.ris.bka.gv.at/GeltendeFassung.wxe?Abfrage=Bundesnormen&Gesetzesnummer=20002763

http://unfccc.int/essential_background/convention/status_of_ratification/items/2631.php

http://unfccc.int/files/essential_background/kyoto_protocol/application/pdf/kpstats.pdf

http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2013:165:0013:0040:EN:PDF

https://www.ris.bka.gv.at/GeltendeFassung.wxe?Abfrage=Bundesnormen&Gesetzesnummer=10011027

http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2010:334:0017:0119:en:PDF

http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2006:033:0001:0017:EN:PDF



Table 2: Protocols of UNECE Convention on Long-range Transboundary Air Pollution (LRTAP).

Tools of UNECE Convention on Long-range Transboundary Air Pollution (LRTAP)

Parties entered into force

signed/ratified by Austria

1979 Convention on Long-range Transboundary Air Pollution (in Geneva)

51 16.03.1983 13.11.1979 (s) 16.12.1982 (r)

1984 Geneva Protocol on Long-term Financing of the Cooperative Programme for Monitoring and Evaluation of the Long-range Transmission of Air Pollutants in Europe (EMEP)

47 28.01.1988 04.06.1987 (ac)

1985 Helsinki Protocol on the Reduction of Sulphur Emis-sions or their Transboundary Fluxes by at least 30 per cent

25 02.09.1987 09.07.1985 (s) 04.06.1987 (r)

1988 Sofia Protocol concerning the Control of Nitrogen Oxides or their Transboundary Fluxes

35 14.02.1991 01.11.1988 (s) 15.01.1990 (r)

1991 Geneva Protocol concerning the Control of Emissions of Volatile Organic Compounds or their Transboundary Fluxes

24 29.09.1997 19.11.1991 (s) 23.08.1994 (r)

1994 Oslo Protocol on Further Reduction of Sulphur Emissions

29 05.08.1998 14.06.1994 (s) 27.08.1998 (r)

1998 Aarhus Protocol on Heavy Metals 34 29.12.2003 24.06.1998 (s) 17.12.2003 (r)

1998 Aarhus Protocol on Persistent Organic Pollutants (POPs)

33 23.10.2003 24.06.1998 (s) 27.08.2002 (r)(1)

1999 The 1999 Gothenburg Protocol to Abate Acidi-fication, Eutrophication and Ground-level Ozone

27 17.05.2005 01.12.1999 (s)

Abbreviation: signed (s) ratified (r) accession (ac) Footnote: (1) with declaration upon ratification Source: http://www.unece.org/env/lrtap/status/lrtap_s.html

1.2.2.1 Reporting obligation under the UNECE/LRTAP Convention and its Protocols

As a minimum requirement, each Party shall report on emissions of the substances relevant to the Protocol to which they are a Party, as required by that Protocol. Since Austria has ratified all protocols to the UNECE/LRTAP Convention (with the exception of the Gothenburg Protocol), the annual reporting obligation enfolds emission data of four groups: main pollutants, particulate matter (PM), heavy metals, and POPs. Table 3, taken from the Reporting Guidelines, gives the present set of components which have to be reported (minimum) and which should be reported voluntarily (additionally).

This report follows the regulations under the UNECE/LRTAP Convention and its Protocols that define standards for national emission inventories. In 2008, the Executive Body adopted the Guidelines for Reporting Emission Data under the Convention on Long-Range Transboundary Air Pollution (LRTAP) (ECE/EB.AIR/97)38/39 for estimating and reporting of emission data. They are necessary to ensure transparency, accuracy, consistency, comparability and completeness (TACCC) of the reported emissions. In 2014 the Reporting Guidelines were revised (ECE/EB.AIR.125)40 and were adopted for application in 2015 and subsequent years.

38 http://www.ceip.at/fileadmin/inhalte/emep/reporting_2009/Rep_Guidelines_ECE_EB_AIR_97_e.pdf 39 At its twenty-sixth session (15–18 December 2008), the Executive Body approved the revised Guidelines

(ECE/EB.AIR/2008/4) as amended at the session and requested the secretariat to circulate a final amended version. 40 http://www.ceip.at/fileadmin/inhalte/emep/2014_Guidelines/ece.eb.air.125_ADVANCE_VERSION_reporting_

guidelines_2013.pdf

http://www.unece.org/env/lrtap/status/lrtap_s.html

http://www.ceip.at/fileadmin/inhalte/emep/reporting_2009/Rep_Guidelines_ECE_EB_AIR_97_e.pdf





The data presented in this report were compiled according to the Reporting Guidelines for esti-mating and reporting emission data, which also define the new reporting format (Nomenclature for Reporting – NFR (latest version of the templates ‘NFR19’41 dated 18.11.2019)) as well as standards for providing supporting documentation which should ensure the transparency of the inventory.

Table 3: Emission Reporting Programme.

Element(s) Pollutant(s) Years (1)

A. National total emissions

1. Main pollutants SOx, NOx, NH3, NMVOC, CO from 1990 to 2017

2. Particulate matter PM2.5, PM10, (TSP, BC) for 1990, 1995, and for 2000 to 2017

3. Heavy metals Pb, Cd, Hg, (As, Cr, Cu, Ni, Se, Zn) from 1990 to 2017

4. POPs PCDD/PCDF, PAHs (2), HCB, PCBs from 1990 to 2017

B. Emissions by NFR source category

1. Main pollutants SOx, NOx, NH3, NMVOC, CO from 1990 to 2017

2. Particulate matter PM2.5, PM10, (TSP, BC) for 1990, 1995, and for 2000 to 2017

3. Heavy metals Pb, Cd, Hg, As, Cr, Cu, Ni, Se, Zn from 1990 to 2017

4. POPs PCDD/PCDF, PAHs (2), HCB, PCBs from 1990 to 2017

C. Activity data by source category from 1990 to 2016

D. Gridded data in the EMEP 0.1x0.1 long/lat grid

1. Sector emissions SOx, NOx, NH3, NMVOC, CO, PM10, PM2.5, Pb, Cd, Hg, PCDD/F, PAHs, HCB, PCBs

2000 (optional) , 2005, 2010, 2015 and every 4 years 2. National totals

E. Emissions from large point sources

SOx, NOx, NH3, NMVOC, CO, PM10, PM2.5, Pb, Cd, Hg, PCDD/F, PAHs, HCB, PCBs

2000 (optional) , 2005, 2010, 2015 and every 4 years

ADDITIONAL REPORTING/FOR REVIEW AND ASSESSMENT PURPOSES

VOC speciation/Height distribution/Temporal distribution

Land-use data/Mercury breakdown

% of toxic congeners of PCDD/F emissions

Pre-1990 emissions of PAHs, HCB, PCDD/F and PCB

Information on natural emissions

41 http://www.ceip.at/ms/ceip_home1/ceip_home/reporting_instructions/




Element(s) Pollutant(s) Years (1)

A. National total emissions

Projected emissions and projected activity data

1. National total emission projections

SOx, NOx, NH3, NMVOC, PM2.5 and BC where appropriate

2020, 2025, 2030, and where available also for 2040 and 2050

2. Emission projections by NFR19

SOx, NOx, NH3, NMVOC, PM2.5 and BC where appropriate


3. Projected activity data by NFR19


(1) As a minimum, data for the base year of the relevant protocol and from the year of entry into force of that protocol to the latest year should be reported

(2) polycyclic aromatic hydrocarbons (PAHs) {benzo(a)pyrene, benzo(b)fluoranthene, benzo(k)fluoranthene, indeno(1,2,3-cd)pyrene,Total 1-4}

1.2.2.2 Reporting obligation under Directive (EU) 2016/2284 on the reduction of national emissions of certain atmospheric pollutants (NEC-Directive)

According to Article 8 of NEC Directive 2016/2284 and Annex I, Table A, Member States shall prepare and annually update national emission inventories for the pollutants SOx, NOx, NH3, NMVOC, CO, heavy metals (Cd, Hg, Pb), POPs (total PAHs, PCBs, HCB), PM2,5, PM10 and, if available, BC. Austria reports the national emission totals calculated on the basis of fuel used (thus excluding emissions from fuel exports in the vehicle tank) for compliance assessment un-der the NEC Directive.

Additionally, Member States shall prepare and update every four years spatially disaggregated national emission inventories and large point source inventories and, every two years, national emission projections for part of these pollutants as set out in the NEC Directive 2016/2284, An-nex I, Table C.

Member States’ submissions of national emission inventories and projections shall be accom-panied by an informative inventory report (this report). The report follows the regulations under the UNECE/LRTAP Convention and its Protocols that define standards for national emission in-ventories (see chapter 1.2.2.1).



1.3 Inventory Preparation Process

The present Austrian Air Emission Inventory (OLI) for the period 1990 to 2018 was compiled according to the recommendations for inventories as set out by the UNECE Executive Body42 and in the guidelines mentioned above.

The preparation of the inventory includes the following three stages as illustrated below.

Figure 3: Three stages of inventory preparation.

I Inventory planning

In the first stage, specific responsibilities are defined and allocated: as mentioned before, the Umweltbundesamt has the overall responsibility for the national inventory, comprising green-house gases as well as other air pollutants.

Inventory planning also includes planning of how to distribute available resources, and thus, as resources are limited, also includes a prioritization of planned improvements, whereby the key category analysis is an important tool.

Within the inventory system, specific responsibilities for the different emission source categories are defined (“sector experts”) as well as for all activities related to the preparation of the invento-ry, including QA/QC, data management and reporting.

Roles and responsibilities within NISA

Figure 4: Roles and responsibilities within the National Emission Inventory System Austria (NISA). 42 http://www.ceip.at/ms/ceip_home1/ceip_home/reporting_instructions/

NIR project managerMethodological

IIR project managerMethodological

OLI project managerTechnical

pollutant expert

Transport

Industrial ProcessesSolvents

AgricultureLULUCFWaste

Fugitives

sector expert

─ CO2─ CH4─ N2O─ F-gasses

─ SO2─ NOx─ NMVOC─ NH3─ CO

─ Heavy metals─ POPs─ Particular matter






















PM, HM & POPs

Energy

I. Inventory planning

II. Inventory

preparation

III. Inventory

management



Particulate matter

Three stages of inventory preparation

F-gases




Emissions of air pollutants are estimated together with greenhouse gases in a single data base based on the CORINAIR43 scheme, which was formerly also used as reporting format under the UNECE. This nomenclature was designed by the ETC/ACC44 to estimate emissions of all kind of air pollutants as well as greenhouse gases.

The CORINAIR system’s nomenclature is called SNAP,45 which may be expanded to adapt to national circumstances by so-called SPLIT codes, and additionally each SNAP/SPLIT category can be extended using a fuel code.

II Inventory preparation

In the second stage, the inventory preparation process, sector experts collect activity data, emis-sion factors and all relevant information needed for finally estimating emissions. The sector ex-perts are also responsible for methodological choices and for contracting studies, if needed.

As the source of emission factors and/or the methodology of emission estimation for HM, POPs and PM is different compared to the “main” pollutants for a lot of source categories, emission in-ventories for these pollutants were prepared in studies that were contracted out; however, the incorporation into the inventory system and the update of emission calculations for subsequent years is the responsibility of the sector experts.

All data collected together with emission estimates are fed into a database (see below), where data sources are documented for future reconstruction of the inventory.

As mentioned above, the Austrian Inventory is based on the SNAP systematic, and has to be transformed into the current reporting format under the LRTAP Convention and the NEC Di-rective – the NFR46 format.

In addition to actual emission data, background tables of the NFR are filled in by the sector ex-perts, and finally QA/QC procedures as defined in the inventory planning process are carried out before the data is submitted under the UNECE/EC.

The following table gives an overview on the tasks of inventory preparation together with a typi-cal timeline.

Table 4: Overview Inventory related tasks.

Task Description Deadline Management Review Preparation of a report including evaluation of the fulfilment

of the previous improvement plan and a plan for QMS and inventory improvement, i.a. based on audit and review findings.

Summer

Kick-Off Meeting of inventory team (sector experts, deputies, project-/quality- and data managers of the inventory); definition of a working plan

End of Summer

Activity data collection Collection of activity data, including contracting out studies. November 15 Inventory preparation Estimation of emissions for all sources, including collection

of background data. December 15

43 CORINAIR: CORINE – CO-oRdination d'INformation Environnementale and include a project to gather and organ-

ise information on emissions into the air relevant to acid deposition; Council Decision 85/338/EEC (OJ, 1985) 44 European Topic Centre on Air Emissions 45 SNAP (Selected Nomenclature for sources of Air Pollution) 90 or 97 respectivley means the stage of development 46 NFR – Nomenclature For Reporting – is a classification system developed by the UN/ECE TFEIP for the Reporting

Guidelines described in eb.air.ge.1.2001.6.e.doc



Task Description Deadline Compilation of national inventory

Updating the data base and generating NFR data files December 23

Quality checks Tier 1 and Tier 2 QA/QC activities December Submission NFR tables Finalization NFR tables and submission to UNECE/EC February 15 Preparation of IIR Compilation of the Informative Inventory Report January–March Submission IIR Submission ot the Informative Inventory Report to the EC

(NEC Directive) and UNECE March 15

III Inventory management

For the inventory management, a reliable data management scheme is needed to fulfil the data collecting and reporting requirements.

Data management is carried out using MS ExcelTM spreadsheets in combination with Visual BasicTM macros, which is a very flexible system that can be adjusted easily to new requirements. The data is stored on a central network server which is backed up continuously for the needs of data security. The inventory management also includes quality management (see Chapter 1.6) as well as documentation on QA/QC activities.

1.4 Methodologies and Data Sources Used

The main data supplier for the Austrian Emission Inventories is Statistik Austria, providing the underlying energy source data. The Austrian energy balances are based on several data-bases mainly prepared by e-Control and Statistik Austria. Their methodology follows the IEA and Eurostat conventions. The aggregated balances, for example transformation input and output or final energy use, are harmonised with the IEA tables as well as their sectoral break-down which follows the NACE classification.

Information about activity data and emissions of the industry sector is mostly obtained directly from individual plants, or in other cases, from Associations of the Austrian Industries. Activity data for some sources are obtained from Statistik Austria which provides statistics on produc-tion data47.

Operators of steam boilers with more than 50 MW report their emissions and their activity da-ta directly to the Umweltbundesamt. Data from national and sometimes international studies are also used.

Until 2008, operators of landfill sites reported their activity data directly to the Austrian Minis-try of Environment or the Umweltbundesamt, where they were – after a check – in turn incor-porated into a database on landfills. Emissions for the years 1998–2007 are calculated on basis of these data. Since 2009 landfill operators have to register and report their waste input directly at the portal of the Electronic Data Management. These data are evaluated by the re-sponsible body at federal level (BMNT) and are made available for emission calculation.

Activity data needed for the calculation of non-energetic emissions are based on several sta-tistics collected by Statistik Austria and national and international studies.

The following table presents the main data sources used for activity data:

47 „Industrie und Gewerbestatistik” published by STATISTIK AUSTRIA for the years until 1995; „Konjunkturstatistik im

produzierenden Bereich” published by STATISTIK AUSTRIA for the years since 1997.



Table 5: Main data sources for activity data.

Sector Data Sources for Activity Data

Energy Energy Balance from Statistik Austria EU-ETS Steam boiler database Small scale combustion market data Direct information from industry or associations of industry

Transport Energy Balance from Statistik Austria

Yearly growth rates of transport performance on Austrian roads from Austrian Ministry for Transport, Technology and Innovation

ZBD: Zentrale Beguchtachtungsdatenbank (yearly specific mileage) Flight movements from AustroControl

IPPU National production statistics Import/export statistics EU-ETS Direct information from industry or associations of industry Short term statistics for trade and services Austrian foreign trade statistics Structural business statistics Surveys at companies and associations Amount of taxed tobacco products

Agriculture National studies National agricultural statistics obtained from Statistik Austria National fertilizer statistics obtained from Agrarmarkt Austria (AMA) Distributing company (sales data)

Waste Federal Waste Management Plan (Data sources: Database on landfills (1998–2007), Electronic Data Management (EDM) in environment and waste management)

EMREG-OW (Electronic Emission Register of Surface Water Bodies) Death statistics

Emission calculation and related inventory work (reporting, QA/QC, documentation and archiv-ing etc.) is carried out by the IBE sector experts.

In cases where the IBE’s capabilities or resources are exceeded, some of its inventory activities are subcontracted, in some cases routinely (e.g. the emission inventory for road transport), in other cases as required (e.g. revision of methodologies for a complex emission source). Such subcontracts have so far been concluded with: Technical University Graz (road and off-road transport) Technical University of Natural Resources and Applied Life Sciences, Research Center

Seibersdorf (Agriculture) Institute for Industrial Ecology (Product Use) Amon and Hörtenhuber 2019 (Agriculture)

However, the final assessment of fulfilment of the requirements is made by the IBE.

Detailed information on data sources for activity and emission data or emission factors used by sector can be found in Chapters 3–6.



For large point sources the Umweltbundesamt preferably uses – after careful assessment of plausibility of this data – emission data that are reported by the ‘operator’ of the source because these data usually reflect the actual emissions better than data calculated using general emission factors, as the operator has the best information about the actual circumstances.If such data is not available, and for area sources, national emission factors are used or, if there are no na-tional emission factors, international emission factors are used to estimate emissions. Where no applicable data is found, standard emission factors e.g. from the EMEP/EEA 2019 Guidebook were applied. The main sources for emission factors are: National studies for country specific emission factors Plant-specific data reported by plant operators IPCC 2006 Guidelines for National Greenhouse Gas Inventories48 EMEP/EEA air pollutant emission inventory guidebook – 2009. Technical report No 9/200949 EMEP/EEA air pollutant emission inventory guidebook – 2013. Technical report No. 12/201350 EMEP/EEA air pollutant emission inventory guidebook – 2016. Technical report No. 21/201651 EMEP/EEA air pollutant emission inventory guidebook – 2019. Technical report No. 21/201952 Handbook emission factors for road transport (HBEFA), Version 4.1

Table 6 presents a main overview of the methods applied and the origin of emission factors used for the categories in the NFR format for the present Austrian inventory.

For key source categories (see chapter 1.5) the most accurate methods for the preparation of the air emission inventory should be used. Required methodological changes and planned im-provements are described in the corresponding sector analysis chapters (Chapters 3–6).

1.4.1 EU Emissions Trading System (EU ETS)

The European Union Emissions Trading Scheme has been established by Directive 2003/87/EC of the European Parliament and of the Council[1] and amended by Directive 2009/29/EC53. From 2013 onwards, it is known as the European Union Emissions Trading System (EU ETS). It in-cludes heavy energy-consuming installations in power generation and manufacturing. The activi-ties covered are energy activities, the production and processing of ferrous metals, the mineral industry and some other production activities. From 2012 onwards, CO2 emissions from aviation have also been included. For the trading period 2013–2020 the scope of the EU ETS has been further extended to include additional installations from the metal and chemical industry and compressor stations. For more detailed information on the included activities please refer to An-nex I of the above mentioned directive.

48 http://www.ipcc-nggip.iges.or.jp/public/2006gl/index.htm 49 http://www.eea.europa.eu/publications/emep-eea-emission-inventory-guidebook-2009 50 http://www.eea.europa.eu/publications/emep-eea-guidebook-2013 51 http://www.eea.europa.eu/publications/emep-eea-guidebook-2016 52 https://www.eea.europa.eu/publications/emep-eea-guidebook-2019

[1] Directive 2003/87/EC of the European Parliament and of the Council of 13 October 2003 establishing a scheme for greenhouse gas emission allowance trading within the Community and amending Council Directive 96/61/EC, OJ L 275/32

53 Directive 2009/29/EC of the European Parliament and of the Council of 23 April 2009 amending Directive 2003/87/EC so as to improve and extend the emission allowance trading scheme of the Community, OJ L 140/63

http://www.ipcc-nggip.iges.or.jp/public/2006gl/index.htm

http://www.eea.europa.eu/publications/emep-eea-emission-inventory-guidebook-2009

http://www.eea.europa.eu/publications/emep-eea-guidebook-2013




Greenhouse gases covered under the EU ETS are CO2 (since 2005), N2O (since 2010) and PFC (since 2013)[2]. About one third of total Austrian GHG emissions currently result from instal-lations under the EU-ETS (~28,5 Mt CO2 in 2018).

Plant operators have to report their activity data and emissions annually for the GHG as men-tioned above; for the first time they reported their emissions of 2005 in March 2006. The first trading period of the EU ETS ran from 2005–2007. The second trading period, which coincided with the 1st Kyoto commitment period, ran from 2008–2012. The third trading period, which co-incides with the 2nd Kyoto commitment period, runs from 2013 to 2020. Since 2012 aircraft op-erators have also been included into the scheme. They have to report their emissions concern-ing internal flights in the European Economic Area.

General rules for reporting and verification of emissions in the EU ETS are defined in EU Directive 2003/87/EC and specific rules can be found in Commission Regulation (EU) No 601/201254. In Austria, Member State specific regulations are defined in the Austrian Emissions Allowance Trading Act55 and the Austrian Monitoring, Reporting and Verification Ordinance56. This ordinance also specifies that the Umweltbundesamt has to incorporate, as far as necessary, the verified emissions of the emissions trading scheme into the national greenhouse gas inventory. For a detailed description of the sectors covered and the incorporation of these emissions into the na-tional inventory please refer to the chapters 3 Energy (CRF Sector 1) and 4 Industrial Process-es and Product Use (CRF Sector 2).

An important feature of the emissions reported under the EU-ETS is that these emissions have to pass independent verification by an accredited verifier. The Austrian Federal Ministry for Sus-tainability and Tourism is in charge of granting the licence to independent verifiers. In addition, the Ministry has to fulfil a quality control function, which is implemented by spot checks of emis-sions and verification reports that the Umweltbundesamt performs on behalf of the Ministry.

1.4.2 Electronic Data Management (EDM)

The electronic data management of the Federal Ministry of Sustainability and Tourism (BMNT) is an electronic recording and notification system (information network), implemented as an in-tegrated e-government application. It allows enterprises and authorities to handle registration and notification obligations online in the areas of waste and environment (e.g. on Austrian Emissions Allowances, HFC or EMREG – Emission Register Surface Water). Data from this source are used for reporting in the sector Waste (e.g. landfilled and biologically treated amounts).

There are around 40 000 users registered, covering national and international waste owners (collectors, operators of treatment plants, waste producers) doing their reporting obligations ac-cording to national legislation, e.g. on landfilled amounts.

[2] Austria unilaterally opted-in N2O as of 2010. Since 2013 N2O and PFCs have been included in the EU ETS at EU level.

54 Commission Regulation (EU) No 601/2012 of 21 June 2012 on the monitoring and reporting of greenhouse gas emissions pursuant to Directive 2003/87/EC of the European Parliament and of the Council.

55 Emissionszertifikategesetz 2011, Federal Law Gazette I No. 118/2011, as amended 56 Überwachungs-, Berichterstattungs- und Prüfungs-Verordnung, Federal Law Gazette II No. 339/2007, as amended

http://www.emissionshandelsregister.at/static/cms/sites/emissionshandelsregister.at/media/download_center/rechtliches/recht_national/UeBPV_Nr_339_2007.pdf



1.4.3 Other data (E-PRTR)

The European Pollutant Release and Transfer Register (E-PRTR) is the EU-wide register con-taining key environmental data from industrial facilities in European Union Member States and in Iceland, Liechtenstein, Norway, Serbia and Switzerland. It was established through the E-PRTR Regulation (EC) No 166/2006.

E-PRTR was preceded by the European Pollutant Emission Register (EPER), with reporting years 2001 or 2002 and 2004. It covers 91 pollutants from nine activity groups, including all pol-lutants reported already under EPER. However, emissions only have to be reported if they ex-ceed certain thresholds. In contrast to EPER, E-PRTR also includes data on releases to land, accidental releases, waste transfers and diffuse emissions57.

Umweltbundesamt implemented E-PRTR in Austria using an electronic system enabling the fa-cilities and the authorities to fulfil the requirements of the E-PRTR Regulation online. In 2008, installations reported for the first time releases and transfers of pollutants and waste from 2007 under the E-PRTR, which is an annual reporting obligation. The plausibility of the reports is checked by the competent authorities and Umweltbundesamt. Umweltbundesamt also checks the data for consistency with other reporting obligations, across the years and across facilities with the same activity. Since submission 2018 data from E-PRTR or its predecessor have been used in one source category (NFR 2.B.10 for NMVOC). The main reason for not using E-PRTR data on a broader scale in the national inventory is that the E-PRTR reports contain only very little information oth-er than emission data, whereby these emissions can either be reported as estimated, measured or calculated emissions. Activity data are often reported in units not useful for the inventory, and also the type of activity data may be different between producers of the same product. In addi-tion, E-PRTR data is not complete for IPCC sectors and it is difficult to include this point source information because no background information (such as fuel consumption data) is available. Furthermore the reporting thresholds are relatively high, so that many of the relevant installa-tions do not have to report.

Thus greenhouse gas emission data from the EU Emissions Trading System (see chapter 1.4.1), combined with the top-down approach of the national inventory has been considered to be more reliable and data of EPER/E-PRTR has not been used as a source for point source da-ta for the national inventory, but for verification purposes – where possible.

1.4.4 Literature

National and sometimes international studies are also used as data suppliers (references are given in the sector analysis chapters). Studies on HM, POPs and PM emissions Emissions of HM and some POPs have already been estimated in the course of CORINAIR 1990 and 1994, respectively.58 With these data and other Austrian publications as a basis, comprehensive emission inventories of HM, POPs and PM for different years were prepared by contractors of the Umweltbundesamt and incorporated into the inventory system afterwards. WINDSPERGER, A. et. al. (1999): Entwicklung der Schwermetallemissionen – Abschätzung der

Emissionen von Blei, Cadmium und Quecksilber für die Jahre 1985, 1990 und 1995 gemäß der CORINAIR-Systematik. Institut für Industrielle Ökologie und Österreichisches Forschungs-zentrum Seibersdorf. Wien. (Nicht veröffentlicht).

57 Data can be downloaded from: http://www.umweltbundesamt.at/prtr/ 58 ORTHOFER, R. (1996); HÜBNER, C. (1996); HÜBNER, C. & WURST, F. (1997); HÜBNER, C. (2000)

http://www.umweltbundesamt.at/prtr/



Development of Heavy Metal Emissions – Estimation of emissions of Lead, Cadmium and Mercury for the years 1985, 1990 and 1995 according to the CORINAIR-systematics. Depart-ment for industrial ecology and Austrian Research Centers Seibersdorf. Vienna. (Not pub-lished).

Österreichische Emissionsinventur für Cadmium, Quecksilber und Blei. Austrian emission inventory for Cd, Hg and Pb 1995–2000 prepared by FTU – Forschungs-

gesellschaft Technischer Umweltschutz GmbH. Vienna November 2001 (not published).

HÜBNER, C. (2001): Österreichische Emissionsinventur für POPs 1985–1999. FTU – Forschungs-gesellschaft Technischer Umweltschutz GmbH. Werkvertrag des Umweltbundesamt, IB-650. Wien. (Nicht veröffentlicht).

Austrian emission inventory for POPs 1985–1999. Prepared by FTU – Research Center Technical environment protection (Ltd.). Study commissioned by Umweltbundesamt IB-650. Vienna. (Not published).

WINIWARTER, W.; TRENKER, C.; HÖFLINGER, W. (2001): Österreichische Emissionsinventur für Staub. Österreichisches Forschungszentrum Seibersdorf. Wien.

Austrian emission inventory for PM. Austrian Research Centers Seibersdorf. Vienna.

WINIWARTER, W.; SCHMID-STEJSKAL, H. & WINDSPERGER, A. (2007): Aktualisierung und Ver-besserung der österreischen Luftschadstoffinventur für Schwebstaub. Systems research – Austrian Research Centers & Institut für Industrielle Ökologie. Wien.

Updating and Improvement of the Austrian Air Emission Inventory (OLI) for PM. Systems re-search – Austrian Research Centers & Department for industrial ecology. Vienna.

1.4.5 Summary of methodologies applied for estimating emissions

In Table 6 a summary of methodologies applied for estimating emissions is given. The following abbreviations are used: D DEFAULT L Literature CS COUNTRY SPECIFIC PS PLANT SPECIFIC

Dark shaded cells indicate that no such emissions arise from this source; light shaded cells in-dicate key sources.

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Table 6: Summary of methodologies applied for estimating emissions.

NFR Description SO2 NOx NMVOC NH3 CO Cd Hg Pb PAH DIOX HCB PCB TSP PM10 PM2.5

1.A.1.a Public Electricity and Heat Production

D/PS, CS

PS, CS CS CS PS, CS D/CS D/CS D/CS L/CS L/CS L/CS D/CS PS, CS PS, CS PS, CS

1.A.1.b Petroleum refining PS PS CS PS D CS CS L/CS L/CS CS CS PS PS PS

1.A.1.c Manufac.of Solid fuels a. Oth. Energy Ind.

D/CS CS CS CS CS D D D D L/CS CS CS CS CS CS

1.A.2 mobile

Other mobile in industry

D/CS CS CS CS CS CS CS CS L/CS L/CS CS L/CS CS CS CS

1.A.2 stat Manuf. Ind. & Constr. –stationary

D/PS, CS

PS, CS PS, CS CS PS, CS D/CS D/CS D/CS L/CS L/CS CS D/CS PS, CS PS, CS PS, CS

1.A.3.a Civil Aviation CS CS CS CS CS CS CS CS CS CS CS

1.A.3.b.1 R.T., Passenger cars CS CS CS CS CS CS CS CS L/CS L/CS CS D CS CS CS

1.A.3.b.2 R.T., Light duty vehicles

CS CS CS CS CS CS CS CS L/CS L/CS CS D CS CS CS

1.A.3.b.3 R.T., Heavy duty vehicles

CS CS CS CS CS CS CS CS L/CS L/CS CS D CS CS CS

1.A.3.b.4 R.T., Mopeds & Motorcycles

CS CS CS CS CS CS CS CS L/CS L/CS CS D D D D

1.A.3.b.5 R.T., Gasoline evaporation

CS

1.A.3.b.6 R.T., Automobile tyre and break wear

CS D D D

1.A.3.b.7 R.T., Automobile road abrasion

L L L D D D

1.A.3.c Railways CS CS CS CS CS D/CS D/CS D/CS L/CS L/CS CS D/CS CS CS CS

1.A.3.d Navigation CS CS CS CS CS CS CS CS L/CS L/CS CS D/CS CS CS CS

1.A.3.e Other transportation D PS/CS CS CS CS D D D D CS CS CS CS CS CS

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1.A.4 mob

Other Sectors – mobile

CS CS CS CS CS CS CS CS L/CS L/CS CS CS CS CS CS

1.A.4 stat

Other Sectors –stationary

D/CS CS CS CS CS D/CS D/CS D/CS L/CS L/CS CS D/CS CS CS CS

1.A.5 Other CS CS CS CS CS CS CS CS L/CS L/CS CS L/CS CS CS CS

1.B FUGITIVE EMISSIONS

PS D, PS CS CS CS

2.A MINERAL PRODUCTS

CS CS CS

2.B CHEMICAL INDUSTRY

CS CS CS PS CS CS CS CS CS CS CS

2.C METAL PRODUCTION

CS CS CS CS CS CS CS CS CS CS D CS CS CS

2.D NON ENERGY PRODUCTS FROM FUELS AND SOLVENT USE

CS CS PS CS

2.G Other product manufacture and use

D D D D D D D D D D D D D

2.H Other Processes CS L CS CS CS CS CS CS CS

2.I Wood processing CS CS CS

3.B.1 Cattle T2 CS/D CS L L L

3.B.2 Sheep T2 CS/D T2 L L L

3.B.3 Swine T2 CS/D CS L L L

3.B.4.d Goats T2 CS/D T2 L L L

3.B.4.e Horses T2 CS/D T2 L L L

3.B.4.g Poultry T2 CS/D T2 L L L

3.B.4.h Other animals T2 CS/D T2 L L L

3.D AGRICULTURAL SOILS

D CS/D CS/D D D/L D/L D/L

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3.F Field burning of agricultural residues

CS/D CS/D CS/D CS/D CS/D CS/D CS/D CS/D CS/D CS/D CS/D CS/D CS/D CS/D

3.I Agriculture – Other

5.A Solid waste disposal on land

CS CS CS CS CS CS

5.B Biological treatment of waste

CS

5.C Waste Incineration D/CS CS CS CS CS D/CS CS CS CS CS CS D CS CS CS

5.D Wastewater handling CS/D

5.E Other waste CS/D CS/D CS/D CS/D CS/D CS/D CS/D



1.5 Key Category Analysis

The identification of key categories is described in the “EMEP/EEA air pollutant emission inven-tory guidebook 2016” (EEA 2016)”. It stipulates that a key category is one that is prioritised with-in the national inventory system because its is significantly important for one or a number of air pollutants in a country's national inventory of air pollutants in terms of the absolute level, the trend, or the uncertainty in emissions (EEA 2016). Furthermore, it is good practice to identify the national key categories in a systematic and objective manner. This can be

achieved by a quantitative analysis of the relationship between the magnitude of emission in any year (level) and the change in emission year to year (trend) of each category’s emissions compared to the total national emissions;

to focus the available resources for improvement in data and methods on categories indenti-fied as key. The identification of key categories in national inventories enables the limited re-sources available for preparing inventories to be prioritised; more detailed, higher tier meth-ods can the be slected for key categories. Invetory compilers should use the category specific methods presented in sectoral decision tress Iin the sectoral volumes;

that the analysis should be performed at the level of NFR categories or subcategoreis at which the guidebook methods and decision trees are provided in the sectoral volumes. Where possible, some categories should be disaggregated by main fuel types;

that each air pollutant emitted from each category should be considered separately; that for each key category, the inventory compiler should determine if certain subcategoreis

are particulary significant usually, for this purpose, the subcategories should be ranked ac-cording to their contribution to the aggregate key categories. Those subcategoreis that con-tribute together more than 60% to the key category should be treated as particularly signifi-cant. It may be appropriate to focus efforts towards methodological improvements of these most significant subcategories.

All notations, descriptions of identification and results for key categories included in this chapter are based on the latest Inventory Guidebook (EEA 2016).

The identification includes all NFR categories and all reported gases SO2, NOx, NMVOC, NH3, CO PM: TSP, PM10, PM2.5 HM: Cd, Hg, Pb POP: PAH, PCDD/F, HCB, PCB

Used methodology for identification of key categories: Approach 1

The methodology follows the IPCC approach to produce pollutant-specific key categories and covers for both level and trend assessment. In Approach 1, key categories are identified using a predetermined cumulative emissions threshold. Key categories are those which, when summed together in descending order of magnitude, cumulatively add up to 80% of the total level. The suggested aggregation level of analysis for Approach 1 provided in Table 2-1 of Chapter 2 of the EMEP/EEA emission inventory guidebook 2016 was used. No special considerations like disaggregation to main fuel types have been made. For reasons of transparency, the same level of aggregation for all pollutants was used.



The presented key category analysis was performed by the Umweltbundesamt with data for air emissions of the submission 2019 to the UNECE/LRTAP and the European Commission. For all gases a level assessment for all years 1990 (base year) and 2017 (last year), as well as a trend assessment for 1990 to 2017 was prepared.

1.A Combustion Activities

1.A Combustion Activities is the most important sector for emissions reported to UNECE and EC. To account for this fact and help prioritising efforts this sector was analysed in greater de-tail.

Furthermore, for mobile sources the different means of transport were considered separately, and additionally the sub category road transport was further disaggregated as it is an important source for many pollutants.

For stationary sources a split following the forth level of the NFR was used (1.A.2.g, 1.A.4.a, b, c).

NFR Description NFR Description

1.A.1.a Public Electricity and Heat Production 1.A.3.a Civil Aviation – LTO (internatinal and domestic)

1.A.1.b Petroleum refining 1.A.3.b.1 R.T., Passenger cars

1.A.1.c Manufacture of Solid fuels and Other Energy Industries

1.A.3.b.2 R.T., Light duty vehicles

1.A.2.a Iron and Steel 1.A.3.b.3 R.T., Heavy duty vehicles

1.A.2.b Non-ferrous Metals 1.A.3.b.4 R.T., Mopeds & Motorcycles

1.A.2.c Chemicals 1.A.3.b.5 R.T., Gasoline evaporation

1.A.2.d Pulp, Paper and Print 1.A.3.b.6 R.T., Automobile tyre and break wear 1.A.2.e Food Processing, Beverages and

Tobacco

1.A.2.g.7 Mobile Combustion in Manufacturing Industries and Construction


1.A.2.g.8 Other Stationary Combustion in Manufacturing Industries and Construction

1.A.3.c Railways

1.A.4.a.1 Commercial/Institutional: Stationary 1.A.3.d Navigation (national navigation and international inland waterway)

1.A.4.a.2 Commercial/Institutional: Mobile 1.A.3.e.1 Pipeline compressors

1.A.4.b.1 Residential: stationary 1.A.5.a Other, Stationary (including Military)

1.A.4.b.2 Residential: Household and gardening (mobile)

1.A.5.b Other, Mobile (including Military)

1.A.4.c.1 Agriculture/Forestry/Fishing: Stationary

1.A.4.c.2 Agriculture/Forestry/Fishing: Off-road Vehicles and Other Machinery

1.A.4.c.3 Agriculture/Forestry/Fishing: National Fishing



1.B Fugitive Emission

For fugitive emissions a split following the third level of the NFR was used.


1.B.1.a Coal Mining and Handling 1.B.2.a Oil

1.B.1.b Solid fuel transformation 1.B.2.b Natural gas

1.B.1.c Other fugitive emissions from solid fuels 1.B.2.c Venting and flaring (Oil and natural gas)

1.B.2.d Other fugitive emissions

2 Industrial Processes and Product Use

For source categories from Industrial procecces a general split following the third level of the NFR was used. As 2.D.3 (Solvents) is an important source for NMVOC emissions, it was broken down into level 4. For the source categories NFR 2.I – NFR 2.L level two of the NFR was used.


2.A.1 Cement Production 2.D.3.a Domestic Solvent Use including Fungicides

2.A.2 Lime Production 2.D.3.b Road Paving with Asphalt

2.A.3 Glass Production 2.D.3.c Asphalt Roofing

2.A.5 Mining, construction/demolition and handling of Product

2.D.3.d Coating applications

2.A.6 Other Mineral Products 2.D.3.e Degreasing

2.B.1 Ammonia Production 2.D.3.f Dry cleaning

2.B.2 Nitric Acid Production 2.D.3.g Chemical products

2.B.3 Adipic Acid Production 2.D.3.h Printing

2.B.4 Carbide Production 2.D.3.i Other Solvent Use

2.B.5 Other 2.H Other Processes

2.B.6 Titanium Dioxide Production 2.I Wood processing

2.B.7 Soda ash Producion 2.J Production of POPs

2.B.10 Other (Handling of products and other chemical industry)

2.K Consumption of POPs and Heavy Metals (e.g. electricial and scientific equipment)

2.C.1 Iron and Steel Production 2.L Other production, consumption, storage, transp. or handling of bulk products

2.C.2 Ferroalloys Production

2.C.3 Aluminium Production

2.C.4 Magnesium Production

2.C.5 Lead Production

2.C.6 Zinc Production

2.C.7 Other Metal Production



3 Agriculture

Level three of the NFR was used; only the sub category 3.B.4 und 3.D.a were further disaggre-gated, as these are important sources for NH3. For 3.B.4 also the methodology is different for the animal categories.


3.B.1 Cattle 3.D.a.1 Inorganic N-fertilizers

3.B.2 Sheep 3.D.a.2 Organic fertilizers

3.B.3 Swine 3.D.a.3 Urine an dung deposited by grazing animals

3.B.4.a Buffalo 3.D.d Off-farm storage, handling and transport of agricultural products

3.B.4.d Goats 3.D.e Cultivated crops

3.B.4.e Horses 3.F Field Burning of agricultural Residues

3.B.4.f Mules and Asses 3.I Agriculture Other

3.B.4.g Poultry

3.B.4.h Other animals

5 Waste

Level two of the NFR was used.


5.A Solid Waste Disposal on Land 5.D Wastewater Treatment

5.B.1 Composting 5.E Other Waste

5.C.1 Waste Incineration

Results of the Level and Trend Assessment (Approach 1)

As the analysis was made for all pollutants reported to the UNECE/EC and as these pollutants differ in their way of formation, most of the identified categories are key for more than one pollu-tant: in total 42 key sources were identified.

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Table 7: Summary of Key Categories for the year 2018 – Contributions per pollutant for Level Assessment (LA) and Trend Assessment (TA) in %.

NFR Code

NFR Category % Contributions to pollutant totals for key categories (cumulative 80%) Sum

of KC

%

contri-butions

Rank

SO2 NOX NMVOC NH3 CO Cd Pb Hg PAH DIOX HCB PCB TSP PM10 PM2.5

LA TA LA TA LA TA LA TA LA TA LA TA LA TA LA TA LA TA LA TA LA TA LA TA LA TA LA TA LA TA

1 A 1 a Public Electricity and Heat Produc-tion

8 8 6 6

12 12 10 10 15 15

4 4

3 3 4 4 6 6 134 3

1 A 1 b Petroleum refining

13 13

26 16

1 A 2 a Iron and Steel 36 36

27 27

127 4

1 A 2 d Pulp, Paper and Print 7 7 13 13 5 5 9 9 67 10

1 A 2 f Non-metallic Min-erals 8 8 4 4 17 17 58 11

1 A 2 g 7 Mobile Combus-tion in Manufactur-ing Industries and Construction

4 4 8 28

1 A 2 g 8

Other Stationary Combustion in Manufacturing In-dustries and Con-struction

11 11 5 5 33 14

1 A 3 b 1 R.T., Passenger cars

36 36 2 2

9 9

2 2 3 3 6 6 118 6

1 A 3 b 2 R.T., Light duty vehicles

7 7

13 24

1 A 3 b 3 R.T., Heavy duty vehicles

11 11

2 2 25 17

1 A 3 b 6 R.T., Automobile tyre and break wear

25 25

5 5 6 6 6 6 82 9

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NFR Code

NFR Category % Contributions to pollutant totals for key categories (cumulative 80%)

Sum of K

C

% contri-

butions

Rank


LA TA LA TA LA TA LA TA LA TA LA TA LA TA LA TA LA TA LA TA LA TA LA TA LA TA LA TA LA TA

1 A 3 b 7 R.T., Automobile road abrasion

4 4 3 3 3 3 21 18

1 A 3 c Railways

4 4 2 2

13 25

1 A 4 a 1 Commer-cial/Institutional: Stationary

2 2 4 33

1 A 4 b 1 Residential: sta-tionary 11 11 7 7 21 21

43 43 20 20 9 9 15 15 72 72 50 50 69 69 18 18 24 24 42 42 800 1

1 A 4 b 2 Residential: Household and gardening (mobile)

4 4

7 29

1 A 4 c 1 Agricultu-tu-re/Forestry/Fishing: Stationary

13 13

6 6

3 3 44 12

1 A 4 c 2

Agricultu-tu-re/Forestry/Fishing: Off-road Vehicles and Other Machin-ery

4 4

2 2 4 4 20 19

2 A 5 Mining, construc-tion/demolition and handling of prod-ucts

34 34 23 23 5 5 123 5

2 C 1 Iron and Steel Production

18 18 32 32 31 31

7 7 10 10 95 95

2 2

390 2

2 C 3 Aluminium produc-tion 10 10 19 20

2 D 3 a Domestic solvent use including fun-

15 15 30 15

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NFR Code

NFR Category % Contributions to pollutant totals for key categories (cumulative 80%)

Sum of K

C

% contri-

butions

Rank


LA TA LA TA LA TA LA TA LA TA LA TA LA TA LA TA LA TA LA TA LA TA LA TA LA TA LA TA LA TA gicides

2 D 3 d Coating applica-tions

5 5

10 27

2 D 3 h Printing 3 3 7 30

2 G Other product manufacture and use

6 6 3 3 18 21

2 H Other Processes

3 3

5 32

2 I Wood processing

3 3

6 31

3 B 1 Cattle

23 23 28 28

101 8

3 B 3 Swine

9 9

18 22

3 D a 1 Inorganic N-fertilizers 7 7 15 23

3 D a 2 Organic fertilizers

4 4 8 8 40 40

102 7

3 D c

On-farm storage, handling and transport of agri-cultural products

9 9 13 13 43 13

5 E Other waste 6 6 12 26

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Table 8: Key Categories for SO2 emissions for the year 2018.

Level Assessment NFR Code

NFR Category Latest Year (2018) Estimate [kt] Ex,t

Level Assessment Lx,t

Cumulative Total of Lx,t

1 A 2 a Iron and Steel 4.26 36.2% 36.2%

1 A 2 g 8 Other Stationary Combustion in Manufacturing In-dustries and Construction 1.35 11.5% 47.7%

1 A 4 b 1 Residential: stationary 1.25 10.6% 58.3%

1 A 1 a Public Electricity and Heat Production 0.96 8.1% 66.4%

1 A 2 f Non-metallic Minerals 0.91 7.7% 74.1%

1 A 2 d Pulp, Paper and Print 0.81 6.9% 81.0%

National Total 11.77

Trend Assessment

NFR Code

NFR Category ‘Base Year‘ (1990) Estimate [kt] Ex,0

Latest Year (2018) Es-timate [kt] Ex,t

Trend Assessment Lx,t

Contribution to the trend


1 A 2 a Iron and Steel 1 A 2 a 6.73 4.26 4.256 36.2%

1 A 2 g 8 Other Stationary Combustion in Manufac-turing Industries and Construction 1 A 2 g 8 1.88 1.35 1.353 11.5%

1 A 4 b 1 Residential: stationary 1 A 4 b 1 25.87 1.25 1.247 10.6%

1 A 1 a Public Electricity and Heat Production 1 A 1 a 11.81 0.96 0.956 8.1%

1 A 2 f Non-metallic Minerals 1 A 2 f 2.23 0.91 0.907 7.7%

1 A 2 d Pulp, Paper and Print 1 A 2 d 4.30 0.81 0.810 6.9%

National Total 73.70 11.77

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Table 9: Key Categories for NOx emissions for the year 2018.

Level Assessment

NFR Code




1 A 3 b 1 R.T., Passenger cars 54.13 35.9% 35.9%

1 A 3 b 3 R.T., Heavy duty vehicles 16.30 10.8% 46.7%


1 A 3 b 2 R.T., Light duty vehicles 9.99 6.6% 60.1%


1 A 4 c 2 Agriculture/Forestry/Fishing: Off-road Ve-hicles and Other Machinery 6.42 4.3% 70.3%

1 A 2 g 7 Mobile Combustion in Manufacturing In-dustries and Construction 6.16 4.1% 74.4%


3 D a 2 Organic fertilizers 5.56 3.7% 81.9%


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Trend Assessment

NFR Code

NFR Category ‘Base Year‘ (1990) Es-timate [kt] Ex,0





1 A 3 b 1 R.T., Passenger cars 60.20 54.13 54.129 35.9% 35.9%

1 A 3 b 3 R.T., Heavy duty vehicles 48.97 16.30 16.301 10.8% 46.7%

1 A 4 b 1 Residential: stationary 15.42 10.29 10.289 6.8% 53.5%

1 A 3 b 2 R.T., Light duty vehicles 7.30 9.99 9.989 6.6% 60.1%

1 A 1 a Public Electricity and Heat Production 12.13 8.92 8.924 5.9% 66.0%

1 A 4 c 2 Agriculture/Forestry/Fishing: Off-road Ve-hicles and Other Machinery 9.42 6.42 6.415 4.3% 70.3%

1 A 2 g 7 Mobile Combustion in Manufacturing In-dustries and Construction 3.03 6.16 6.163 4.1% 74.4%

1 A 2 f Non-metallic Minerals 9.99 5.78 5.778 3.8% 78.2%

3 D a 2 Organic fertilizers 5.80 5.56 5.561 3.7% 81.9%


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Table 10: Key Categories for NMVOC emissions for the year 2018.

Level Assessment

NFR Code




3 B 1 Cattle 24.35 22.7% 22.7%


2 D 3 a Domestic solvent use including fungicides 16.10 15.0% 59.1%


2 D 3 d Coating applications 5.31 5.0% 71.9%

2 D 3 h Printing 3.74 3.5% 75.4%

2 H Other Processes 2.71 2.5% 77.9%



Trend Assessment

NFR Code

NFR Category

‘Base Year‘ (1990) Estimate [kt] Ex,0

Latest Year (2018) Estimate [kt] Ex,t




3 B 1 Cattle 32.77 24.35 24.346 22.7% 22.7%


2 D 3 a Domestic solvent use including fungicides 16.30 16.10 16.096 15.0% 59.1%


2 D 3 d Coating applications 45.79 5.31 5.309 5.0% 71.9%

2 D 3 h Printing 12.65 3.74 3.744 3.5% 75.4%

2 H Other Processes 1.89 2.71 2.706 2.5% 77.9%



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Table 11: Key Categories for NH3 emissions for the year 2018.

Level Assessment

NFR Code





3 B 1 Cattle 17.92 27.7% 67.3%

3 B 3 Swine 5.69 8.8% 76.1%

3 D a 1 Inorganic N-fertilizers 4.81 7.4% 83.6%


Trend Assessment

NFR Code

NFR Category ‘Base Year‘ (1990) Esti-mate [kt] Ex,0






3 B 1 Cattle 13.89 17.92 17.919 27.7% 67.3%

3 B 3 Swine 8.47 5.69 5.693 8.8% 76.1%

3 D a 1 Inorganic N-fertilizers 5.00 4.81 4.813 7.4% 83.6%


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Table 12: Key Categories for CO emissions for the year 2018.

Level Assessment

NFR Code





1 A 2 a Iron and Steel 133.30 27.2% 70.4%


1 A 4 b 2 Residential: Household and gardening (mobile) 17.68 3.6% 83.2%


Trend Assessment

NFR Code







1 A 2 a Iron and Steel 210.72 133.30 133.305 27.2% 70.4%


1 A 4 b 2 Residential: Household and gardening (mobile) 21.71 17.68 17.682 3.6% 83.2%

National Total 1 249.41 490.09

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Table 13: Key Categories for Cd emissions for the year 2018.

Level Assessment

NFR Code

NFR Category Latest Year (2018) Estimate [t] Ex,t




2 C 1 Iron and Steel Production 0.21 18.4% 38.1%

1 A 1 b Petroleum refining 0.15 12.8% 50.9%



2 G Other product manufacture and use 0.07 6.4% 81.8%

National Total 1.13

Trend Assessment

NFR Code

NFR Category

‘Base Year‘ (1990) Es-timate [t] Ex,0

Latest Year (2018) Es-timate [t] Ex,t





2 C 1 Iron and Steel Production 0.46 0.21 0.209 18.4% 38.1%

1 A 1 b Petroleum refining 0.15 0.15 0.145 12.8% 50.9%

1 A 2 d Pulp, Paper and Print 0.15 0.14 0.144 12.7% 63.6%


2 G Other product manufacture and use 0.09 0.07 0.072 6.4% 81.8%


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Table 14: Key Categories for Pb emissions for the year 2018.

Level Assessment

NFR Code





1 A 3 b 6 R.T., Automobile tyre and break wear 4.80 24.9% 57.3%





Trend Assessment

NFR Code

NFR Category ‘Base Year‘ (1990) Estimate [t] Ex,0

Latest Year (2018) Estimate [t] Ex,t





1 A 3 b 6 R.T., Automobile tyre and break wear 2.67 4.80 4.798 24.9% 57.3%





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Table 15: Key Categories for Hg emissions for the year 2018.

Level Assessment

NFR Code









National Total 0.96

Trend Assessment

NFR Code

NFR Category ‘Base Year‘ (1990) Estimate [t] Ex,0






1 A 2 f Non-metallic Minerals 0.70 0.17 0.166 17.3% 47.9%





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Table 16: Key Categories for PAH emissions for the year 2018.

Level Assessment

NFR Code





1 A 4 c 1 Agriculture/Forestry/Fishing: Stationary 0.88 13.0% 85.1%

National Total 6.80

Trend Assessment

NFR Code

NFR Category

‘Base Year‘ (1990) Estimate [t] Ex,0






1 A 4 c 1 Agriculture/Forestry/Fishing: Stationary 0.46 0.88 0.882 13.0% 85.1%


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Table 17: Key Categories for PCDD/F/Furan emissions for the year 2018.

Level Assessment

NFR Code

NFR Category Latest Year (2018) Estimate [g] Ex,t




2 C 3 Aluminium production 3.30 9.6% 59.4%


5 E Other waste 2.06 6.0% 72.6%

1 A 2 g 8 Other Stationary Combustion in Manufac-turing Industries and Construction 1.76 5.1% 77.7%



Trend Assessment

NFR Code

NFR Category ‘Base Year‘ (1990) Estimate [g] Ex,0

Latest Year (2018) Estimate [g] Ex,t





2 C 3 Aluminium production 2.40 3.30 3.296 9.6% 59.4%


5 E Other waste 2.10 2.06 2.058 6.0% 72.6%

1 A 2 g 8 Other Stationary Combustion in Manufac-turing Industries and Construction 0.35 1.76 1.759 5.1% 77.7%



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Table 18: Key Categories for HCB emissions for the year 2018.


NFR Category Latest Year (2018) Estimate [kg] Ex,t



1 A 4 b 1 Residential: stationary 24.51 68.8% 68.8% 2 C 1 Iron and Steel Production 3.54 9.9% 78.7% 1 A 4 c 1 Agriculture/Forestry/Fishing: Stationary 2.30 6.5% 85.2%


Trend Assessment NFR Code

NFR Category ‘Base Year‘ (1990) Estimate [kg] Ex.0

Latest Year (2018) Estimate [kg] Ex.t

Trend Assessment Lx.t


Cumulative Total of Lx.t

1 A 4 b 1 Residential: stationary 50.04 24.51 24.508 68.8% 68.8% 2 C 1 Iron and Steel Production 8.09 3.54 3.537 9.9% 78.7% 1 A 4 c 1 Agriculture/Forestry/Fishing: Stationary 1.88 2.30 2.301 6.5% 85.2%


Table 19: Key Categories for PCB emissions for the year 2018.


NFR Category Latest Year (2018) Estimate [kg] Ex,t



2 C 1 Iron and Steel Production 30.40 94.7% 94.7% National Total 32.09 Trend Assessment NFR Code

NFR Category ‘Base Year‘ (1990) Estimate [kg] Ex.0

Latest Year (2018) Estimate [kg] Ex.t

Trend Assessment Lx.t


Cumulative Total of Lx.t

2 C 1 Iron and Steel Production 19.34 30.40 30.399 94.7% 94.7% National Total 47.23 32.09

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Table 20: Key Categories for TSP emissions for the year 2018.





2 A 5 Mining, construction/demolition and handling of products 12.85 33.5% 33.5% 1 A 4 b 1 Residential: stationary 6.75 17.6% 51.1% 3 D c On-farm storage, handling and transport of agricultural products 3.34 8.7% 59.9% 1 A 3 b 6 R.T., Automobile tyre and break wear 1.94 5.1% 64.9% 1 A 3 b 7 R.T., Automobile road abrasion 1.62 4.2% 69.1% 1 A 3 c Railways 1.61 4.2% 73.3% 2 I Wood processing 1.13 3.0% 76.3% 1 A 1 a Public Electricity and Heat Production 1.09 2.9% 79.1% 1 A 3 b 1 R.T., Passenger cars 0.86 2.2% 81.4%


Trend Assessment NFR Code






2 A 5 Mining, construction/demolition and handling of products 9.97 12.85 12.849 33.5% 33.5% 1 A 4 b 1 Residential: stationary 11.49 6.75 6.752 17.6% 51.1% 3 D c On-farm storage, handling and transport of agricultural products 3.56 3.34 3.340 8.7% 59.9% 1 A 3 b 6 R.T., Automobile tyre and break wear 1.05 1.94 1.935 5.1% 64.9% 1 A 3 b 7 R.T., Automobile road abrasion 0.89 1.62 1.617 4.2% 69.1% 1 A 3 c Railways 2.00 1.61 1.607 4.2% 73.3% 2 I Wood processing 0.92 1.13 1.131 3.0% 76.3% 1 A 1 a Public Electricity and Heat Production 0.83 1.09 1.093 2.9% 79.1% 1 A 3 b 1 R.T., Passenger cars 1.61 0.86 0.859 2.2% 81.4% National Total 53.21 38.32

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Table 21: Key Categories for PM10 emissions for the year 2018.





1 A 4 b 1 Residential: stationary 6.31 23.9% 23.9% 2 A 5 Mining, construction/demolition and handling of products 6.11 23.1% 47.0% 3 D c On-farm storage, handling and transport of agricultural products 3.34 12.6% 59.7% 1 A 3 b 6 R.T., Automobile tyre and break wear 1.46 5.5% 65.2% 1 A 1 a Public Electricity and Heat Production 0.99 3.7% 68.9% 1 A 3 b 1 R.T., Passenger cars 0.86 3.3% 72.2% 1 A 3 b 7 R.T., Automobile road abrasion 0.81 3.1% 75.3% 1 A 3 c Railways 0.57 2.2% 77.4% 1 A 4 c 2 Agriculture/Forestry/Fishing: Off-road Vehicles and Other Machinery 0.51 1.9% 79.3% 2 C 1 Iron and Steel Production 0.49 1.8% 81.2%

National Total 26.40 Trend Assessment NFR Code



Trend Assess-ment Lx,t



1 A 4 b 1 Residential: stationary 10.66 6.31 6.313 23.9% 23.9% 2 A 5 Mining, construction/demolition and handling of products 4.73 6.11 6.106 23.1% 47.0% 3 D c On-farm storage, handling and transport of agricultural products 3.56 3.34 3.340 12.6% 59.7% 1 A 3 b 6 R.T., Automobile tyre and break wear 0.79 1.46 1.456 5.5% 65.2% 1 A 1 a Public Electricity and Heat Production 0.78 0.99 0.985 3.7% 68.9% 1 A 3 b 1 R.T., Passenger cars 1.61 0.86 0.859 3.3% 72.2% 1 A 3 b 7 R.T., Automobile road abrasion 0.44 0.81 0.808 3.1% 75.3% 1 A 3 c Railways 0.96 0.57 0.570 2.2% 77.4% 1 A 4 c 2 Agriculture/Forestry/Fishing: Off-road Vehicles and Other Machinery 2.06 0.51 0.509 1.9% 79.3% 2 C 1 Iron and Steel Production 4.56 0.49 0.486 1.8% 81.2% National Total 40.90 26.40

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Table 22: Key Categories for PM2.5 emissions for the year 2018.





1 A 4 b 1 Residential: stationary 5.98 41.9% 41.9% 1 A 3 b 1 R.T., Passenger cars 0.86 6.0% 48.0% 1 A 1 a Public Electricity and Heat Production 0.82 5.8% 53.7% 1 A 3 b 6 R.T., Automobile tyre and break wear 0.79 5.5% 59.3% 2 A 5 Mining, construction/demolition and handling of products 0.68 4.8% 64.1% 1 A 4 c 2 Agriculture/Forestry/Fishing: Off-road Vehicles and Other Machinery 0.51 3.6% 67.6% 1 A 3 b 7 R.T., Automobile road abrasion 0.44 3.1% 70.7% 2 G Other product manufacture and use 0.41 2.9% 73.6% 1 A 4 c 1 Agriculture/Forestry/Fishing: Stationary 0.37 2.6% 76.1% 1 A 4 a 1 Commercial/Institutional: Stationary 0.29 2.1% 78.2% 1 A 3 b 3 R.T., Heavy duty vehicles 0.27 1.9% 80.1% National Total 14.26 Trend Assessment NFR Code



Trend Assess-ment Lx,t



1 A 4 b 1 Residential: stationary 9.97 5.98 5.980 41.9% 41.9% 1 A 3 b 1 R.T., Passenger cars 1.61 0.86 0.859 6.0% 48.0% 1 A 1 a Public Electricity and Heat Production 0.66 0.82 0.822 5.8% 53.7% 1 A 3 b 6 R.T., Automobile tyre and break wear 0.43 0.79 0.790 5.5% 59.3% 2 A 5 Mining, construction/demolition and handling of products 0.53 0.68 0.684 4.8% 64.1% 1 A 4 c 2 Agriculture/Forestry/Fishing: Off-road Vehicles and Other Machinery 2.06 0.51 0.509 3.6% 67.6% 1 A 3 b 7 R.T., Automobile road abrasion 0.24 0.44 0.437 3.1% 70.7% 2 G Other product manufacture and use 0.54 0.41 0.408 2.9% 73.6% 1 A 4 c 1 Agriculture/Forestry/Fishing: Stationary 0.47 0.37 0.367 2.6% 76.1% 1 A 4 a 1 Commercial/Institutional: Stationary 0.78 0.29 0.294 2.1% 78.2% 1 A 3 b 3 R.T., Heavy duty vehicles 2.46 0.27 0.268 1.9% 80.1% National Total 27.17 14.26



1.6 Quality Assurance, Quality Control and verification

For fulfilment of the reporting obligations the department Climate Change Mitigation & Emission Inventories at the Umweltbundesamt, in particular the Inspection Body for Emission Inventories, operates a QMS based on the International Standard EN ISO/IEC 17020 General Criteria for the operation of various types of bodies performing inspections.

Since 23 December 2005 the Umweltbundesamt has been accredited as Inspection Body for emission inventories, Type A (ID No. 0241), in accordance with EN ISO/IEC 17020 and the Aus-trian Accreditation Law (AkkG) 59, by decree of Accreditation Austria (first decree, No. BMWA-92.715/0036-I/12/2005, issued by Accreditation Austria / Federal Ministry of Economics and La-bour on 19 January 2006).

In addition to the elements of a QMS as described in the ISO 9000 series, the EN ISO/IEC 17020 focusses on the competence of the personnel, and ensures strict independence, impar-tiality and integrity. The implementation is audited by the Austrian Accreditation Body (‘Akkredi-tierung Austria’) regularly every 20 months on average. Every five years the accreditation has to be renewed in a more comprehensive audit. The accreditation of the IBE was awarded for the first time in 2005 and was renewed in 2011 and 2016 so far.

Major elements of the QMS are the Quality Manual of the IBE and its quality and technical pro-cedures (‘Austrian QA/QC Plan’).

1.6.1 Requirements of the ISO compared to the IPCC 2006 GL as well as the EMEP/EEA Air Pollutant Emission Inventory Guidebook 2016

The implementation of QA/QC procedures as required by the IPCC 2006 GL and the EMEP/EEA Air Pollutant Emission Inventory Guidebook 2016 support the development of national air emis-sions inventories that can be readily assessed in terms of quality and completeness. The QMS as implemented in the Austrian inventory includes all elements of the QA/QC system outlined in the 2006 IPCC GL Chapter 6 ‘Quality Assurance and Quality Control’ and the EMEP/EEA Air Pollutant Emission Inventory Guidebook 2016 Chapter 6 ‘Inventory management, improvement and QA/QC’ (see Table below), and goes beyond. It also comprises supporting and management processes in addition to the QA/QC procedures in inventory compilation and thus ensures agreed standards not only within (i) the inventory compilation process and (ii) supporting pro-cesses (e.g. archiving), but also for (iii) management processes (e.g. annual management re-views, internal audits, regular training of personnel, definition of procedures for external com-munication).

59 Federal Law Gazette I No 28/2012 (Akkreditierungsgesetz 2012), last amended by Federal Law Gazette I

No 40/2014



Table 23: Overview of obligatory QAQC elements in different technical and quality standards.

EMEP/EEA GB 201660

IPCC 2006 GL ISO 900161 ISO/IEC 1702062

Roles and Responsi-bilities

Roles and Responsibili-ties

Responsibilities and au-thorities

Organisation and Man-agement

QA/QC plan QA/QC plan Quality manual and quality procedures

Quality manual and quality procedures

QC procedures QC procedures Corrective actions Corrective actions

QA procedures QA procedures Preventive actions Preventive actions

QA/QC system inter-action with uncertainty analysis

QA/QC system interac-tion with uncertainty analysis

- -

Verification activities Verification activities - -

Reporting, document-ing and archiving pro-cedures

Reporting, documenting and archiving proce-dures

Records on product re-alisation

Inspection reports, in-spection records

Inventory manage-ment report63

- Management review (report)

Management review (report)

- - Control of documents and records

Control of documents and records

- - Internal audits Internal audits

- - - Competence

- - - Independence, impar-tiality and integrity

1.6.2 Quality policy and objectives

As stated in the Quality Manual of the IBE, the overall objective of the work of the IBE is to pro-mote, under the Kyoto Protocol, climate change mitigation measures and air quality control. To achieve this, the IBE is committed to strict impartiality and quality management. In this context, the term quality means:

1. Fulfilment of requirements for emission inventories.

2. For the fulfilment of these requirements, the IBE undertakes to keep its staff updated on the latest technical expertise, scientific findings and the latest developments. The IBE will there-fore encourage the participation of its staff in international technical and political processes and ensure the transfer of knowledge within the IBE.

60 Requirements largely based on the ‘Quality Assurance/Quality Control and Verification’ chapter of the 2006 IPCC

Guidelines (IPCC 2006). 61 Basic international standard for quality management and quality assurance 62 contains additional requirements compared to ISO 9001 63 According to the EMEP Guidebook 2016, it also is good practice to summarize lessons learned from previous inven-

tory preparation cycles in an inventory management report.



3. Compliance with the EN ISO/IEC 17020 standard by ensuring the implementation and con-tinuous improvement of a QMS as described in this manual by the IBE and its personnel. The QMS procedures are designed to facilitate the preparation of the emission inventories in a professional and timely manner, particularly to enhance the transparency to allow full re-production, and ensure correctness by applying quality checks and validation activities. One of the key managerial functions is raising the personnel’s awareness for quality control.

Aim of the IBE is to provide a best-practice example by setting a high quality standard – even higher than specified in the requirements – so as to improve the quality of air emission reporting in the long term, and to encourage other countries to set up similar systems.

The quality objectives for emission inventories are above all the fulfilment of all relevant re-quirements in terms of content and format: ‘TACCC’: transparency, accuracy, completeness, comparability, consistency (as defined in the IPCC 2006 GL), and timeliness.

The QMS was primarily developed to meet the requirement of reporting greenhouse gas emis-sions under the Kyoto Protocol. For this reason the emphasis was originally placed on green-house gases, but by now all main air pollutants are covered by the QMS.



1.6.3 Design of the Austrian QMS

The design of the QMS of the Inspection Body for Emission Inventories (IBE) at the Umwelt-bundesamt follows a process based approach (see Figure 5).

The Quality Manual of the Inspection Body for Emission Inventories is published on: http://www.umweltbundesamt.at/umweltsituation/luft/emissionsinventur/emi_akkreditierung/

Figure 5: Process-based QMS of the IBE.

Roles and Responsibilities

The Umweltbundesamt is designated as the single national entity responsible for Austria’s Air Emission Inventory by law, and is thus responsible for QA/QC activities. Within the Umweltbun-desamt, the Inspection Body for Emission Inventories IBE has been established and entrusted with the preparation of emission inventories. Within the IBE, roles and responsibilities of the dif-ferent functions – quality representative, sector expert, sector lead, project manager, head of in-spection body, inventory support – are defined in the QMS as well.


http://www.umweltbundesamt.at/umweltsituation/luft/emissionsinventur/emi_akkreditierung/



1.6.4 QA/QC Plan

Activities to be conducted by the personnel of the IBE are written down in quality and technical procedures that complement the Quality Manual. Such activities are: QC activities Procedures for country specific

methodologies Internal audits (QM specific) Procedures for sub-contracting

Inventory improvement plan Documentation and archiving Treatment of confidential data Annual Management Review

Quality Manual

The Quality System is divided into three levels: Level 1: General (the actual ‘Quality Manual’containing general information, description of

QMS, general responsibilities etc.): http://www.umweltbundesamt.at/umweltsituation/luft/emissionsinventur/emi_akkreditierung/ Level 2: Detailed description of activities to be conducted and checklists and forms to be

filled in (‘quality procedures’ and ‘technical documents’). Level 3: Documentation of QC activities (filled in checklists, ...)

Structure of the Austrian Quality Management System

Figure 6: Structure of the Austrian Quality Management System (QMS).

Quality Manual

Quality Procedures

Technical documents

Records


Approach and Responsibilities

Who? What? When?

How?

Records of Implementation

http://www.umweltbundesamt.at/umweltsituation/luft/emissionsinventur/emi_akkreditierung/



1.6.5 QC Activities

The following four quality-check-steps are performed before finalization of the data submission: (1) Tier 2 (category specific): by the sector expert in the course of the inventory preparation (2) Tier 1 (general) / Step 1: QC by the sector expert after emissions have been estimated (3) Tier 1 (general) / Step 2: QC by the data manager in the course of the preparation of the

overall inventory (electronic checks e.g. check for completeness and comparison with last years’ inventory)

(4) Tier 1 (general) / Step 3: QC of final submission by the sector expert Where possible the checks (1), (2) and (4) are conducted by the sector expert that has not pre-dominantly prepared the sectoral inventory in the particular year.

QC activities are conducted according to QC checklists, which cover issues like: documentation of assumptions documentation of expert judgements clear explanation of recalculations provision of references plausibility of data consistency of data

completeness correct transformation/transcription into NFR

information on background tables consistency of data and information with in-

formation in inspection reports treatment of confidential data

Additionally, in the course of the IIR preparation, the following four QC steps are performed: (1) Tier 2 (category specific) / Step 1: check of methodologies, assumptions and explanations

by sector expert in the course of report preparation (2) Tier 2 (category specific) / Step 2: check of methodologies, assumptions and explanations

by the head of inspection body (3) Tier 1 (general) / Step 1: final check of each sector chapter by the corresponding sector ex-

perts (in particular regarding consistency of values in the NIR and the latest CRF tables) (4) Tier 1(general) / Step 2: final check of consistency of figures in reporting format and report

by a member of the IBE team (usually done by the report coordinator who checks at least 5 values per sector)

If NFR tables are updated during the preparation of the inventory, the data manager informs the whole team immediately to make sure that comparisons between NFR and IIR data are done by sector experts with the latest data set.

1.6.6 QA Activities

The following QA activities are performed:

Validation of methodologies and calculation Before methodologies are applied the methodology is defined as a SOP (standard operating procedure) together with a template for calculating emissions, where needed. The SOP is checked for applicability and completeness of information needed and finally approved by the head of the inspection body. New and changed calculation files are validated before use.



Annual second party audits for every sector

Once a year the documentation of one emission source per sector is checked throughout the whole emission estimation and reporting process (i.e. archiving of underlying information, emis-sion calculation, input into the data management system, documentation, information in the IIR etc.) for transparency, reproducibility, clearness and completeness. This tool has proved to be very helpful in order to further improve the documentation and the implementation of (new) QA/QC routines.

Second party audits for work performed by sub-contractors The sector experts at the Umweltbundesamt are responsible for incorporation of results in the inventory database and additional QA/QC procedures (carried out as second party audit).

Accreditation audits (third party audits) In the course of the accreditation process, conformity of the QMS with ISO/IEC 17020 is regu-larly monitored. Audits are performed every 20 months on average by the accreditation body (one day audit). Every fifth year the accreditation has to be renewed in a more comprehensive audit. The audits aim to assess the QM system with regard to compliance with the underlying standard ISO/IEC 17020, to check its implementation in practice and to assure that measures and recommendations as set out in previous audits have been implemented accordingly.

Audits of data suppliers Suppliers of annual activity data, that do not have in place a (certified) QMS or whose data are not independently verified, are audited in a so called ‘input data audit’. The aim of the audits is to assess: (1) whether the requirements regarding independence and integrity are fulfilled (2) the long term availability of the data (3) the data collection and management process (4) whether the QC requirements of the data processing are fulfilled

When indicated, recommendations for improvements are made and implementation of these measures is assessed. These input data audits have proven a good basis for the cooperation with the data supplier.

Since 2007 all main data suppliers have been audited: Statistik Austria regarding energy balance in 2007 agricultural statistical data in 2009 import/export and production statistics in 2016

the administrator of the landfill database in 2009 the administrator of the electronic data management for landfills (EDM) in 2014 the Institute for Industrial Ecology in 2016 the national forest inventory at the Austrian Federal Office and Research Centre for Forests

(BFW) in 2016

It is planned to conduct a follow-up audit at these institutions only when substantial changes be-come apparent.



1.6.7 Error correction and continuous improvement

All issues regarding transparency, accuracy, completeness, consistency or comparability identi-fied by experts from different backgrounds are incorporated in the inventory improvement plan. Sources of these findings are: UNECE/LRTAP Review: The last In-depth review (stage 3) took place in 2017; the findings

are summarized in Chapter 7.4, Table 320. The stage 1 review (initial check of submissions for timeliness, completeness and formats) and stage 2 review (check of consistency, compa-rability, KCA, trends and IEFs) are carried out annually.

NEC Review: From 2017 onwards the national emission inventory data is also checked by the European Commission as set out in Article 10 of Directive 2016/2284 (NEC Directive). The findings of the NEC Review 2019 are summarized in Chapter 7.4, Table 321.

external experts (e.g. experts from federal provinces who prepare a partly independent emis-sion inventory for their federal province compare their results with the disaggregated national inventory),

stakeholders (e.g. industrial facilities or association of industries: the IIR is communicated to every data supplier and Austrian experts involved in emission inventorying after submission),

personnel of the inspection body (head of inspection body, sector experts etc.).

These findings are documented including a plan to improve the inventory, a timeline and re-sponsibilities. Improvements that are relevant in terms of resources are presented in the annual Management Review to the managing directors, and if additional resources are needed, these are notified to the Federal Ministry ‘Climate Action, Environment, Energy, Mobility, Innovation and Technology’ (BMK).

1.6.8 Archiving and documentation

For each sector the documentation includes: Documentation of the methodology: description (source/sink category, emissions, key source, completeness, uncertainty) methodology template for emission estimation documentation of validation Documentation of actual emission calculation: methodology ‘logbook’ (who did what and when) calculation file references for activity data, emission factors and/or emissions, respectively documentation of assumptions, sources of data and information, expert judgments etc. to allow

full reproduction and understanding of choices, recalculations planned improvements QC activities



Documentation of expert judgements in line with the IPCC 2006 GL and the EMEP/EEA GB 2016: name of the expert and institution/department date basis of judgement (references to relevant studies etc.) underlying assumptions Relevant literature has to be archived and references to be stated in the internal documentation as well as in the IIR.

1.6.9 Treatment of confidentiality issues

The IBE ensures confidential treatment of sensitive information obtained in the course of its in-spection activities. Information or data is declared as confidential when it could directly or indi-rectly identify an individual person, business or organisation. For this reason some emissions are reported at a higher, aggregated level so that confidentiality is no longer an issue, e.g. for fluorinated substances. Compliance with confidentiality provisions is organized and documented in the QM manual, which contains specific quality system procedures. Staff of the inspection body is obliged to issue a written commitment stating their full compliance with all provisions. Confidentiality of statistics

The strict confidentiality provisions concerning handling of sensitive data relating to individu-als and organisations are regulated by the Austrian Federal Statistics Act 200064.

Security of data Confidentiality of sensitive data used to calculate emission is a legal obligation: Ensuring con-fidentiality through technical and organisational measures (e.g. final QC whether confidential information is not visible in the CRF/NFR tables) is obligatory for the Umweltbundesamt and consequently also for the Inspection Body.

Trust of respondents Individuals, associations and organizations providing information to the Inspection Body can be sure that the provided data are used exclusively for purposes of inspection activities. Data – either of official, private or of another nature – are treated confidentially and will not be passed on to third parties.

Also in case of voluntary reviews an absolute confidential treatment of data exchanged is ensured by strictly adhering to the rules of the QM System of the Inspection Body.

1.6.10 QMS activities and improvements 2019

Since 2019 each position in the inspection body has been double staffed (meanwhile 22 experts are directly or indirectly involved in inventory work). Three of these experts were able to gain experience by taking part in the international review process for greenhouse gases (centralized review under the European Effort Sharing Decision, centralized review under article 8 of the Kyoto Protocol and in-country review of the 7th National Communication and the 3rd Biennial Report respectively) and 6 experts took part in the reviews for air pollutants (NEC directive, CLRTAP). Furthermore two experts passed exams of the ‘Training programme for members of expert re-view teams participating in annual reviews under Article 8 of the Kyoto Protocol’. Our senior expert for sector energy was part of an expert team that analyzed ways for improve-ment of the national energy balance provided by the Austrian Statistical Office. 64 Federal Act on Federal Statistics (Federal Statistics Act 2000) no. 163/1999



1.7 Uncertainty Assessment

From submission 2017 onwards a qualitative uncertainty assessment and additionally a quanti-tative uncertainty analysis for the main pollutants (SO2, NOx, NMVOC, NH3 and PM2.5) has been carried out. The submission 2019 first time includes CO, heavy metals and POPs (Cd, Hg, Pb, PAH, DIOX, HCB and PCB) and PMs (TSP and PM10). Information on methodology and data sources used is provided in the following sections.

1.7.1 Method used

The method used for the assessment of uncertainty is described in the “EMEP/EEA air pollutant emission inventory guidebook 2016 (EEA 2016)”.

In the Austrian uncertainty analysis the Tier 1 method was applied for the following pollutants: SO2, NOx, NMVOC, NH3, CO, Cd, Hg, Pb, PAH, DIOX, HCB, PCB, TSP, PM10 and PM2.5. By us-ing the error propagation method, the uncertainties for a specific source category can be esti-mated and by combining these uncertainties an overall uncertainty can be calculated. For the remaining other pollutants a qualitative indication of the uncertainty is presented.

The Tier 2 method (Monte Carlo Simulation) was not included in this assessment as the less comprehensive Tier 1 method already gives a clear reference point of the general uncertainty per pollutant.

1.7.2 Data source

In order to estimate the overall uncertainty, the uncertainty of activity data and emission factor, respectively, has to be quantified. The uncertainties of activity data on sectoral level are based on the GHG uncertainty analysis (for more information see UMWELTBUNDESAMT 2020 a).

Uncertainties of emission factors of the relevant pollutants are based on the qualitative ratings following the EMEP/EEA air pollutant emission inventory guidebook 2016 (EEA 2016). Therefore the arithmetic mean value of the proposed upper and lower emission factor uncertainty was cal-culated and used for the calculation of the overall combined uncertainty.

The quality of estimates for all relevant pollutants has been rated using qualitative indicators as suggested in Chapter 5 of the EMEP/EEA air pollutant emission inventory guidebook 2016 (EEA 2016). The definition of the ratings is given in Table 24, the ratings for the emission estimates are presented in Table 25.

Table 24: Rating definitions.

Rating Definition Typical Error Range A An estimate based on a large number of measurements made at a

large number of facilities that fully represent the sector 10 to 30%

B An estimate based on a large number of measurements made at a large number of facilities that represent a large part of the sector

20 to 60%

C An estimate based on a number of measurements made at a small number of representative facilities, or an engineering judgement based on a number of relevant facts

50 to 200%

D An estimate based on single measurements, or an engineering calculation derived from a number of relevant facts

100 to 300%

E An estimate based on an engineering calculation derived from assumptions only

order of magnitude

Source: Table 3-2 Rating definitions, Chapter 5 of the EMEP/EEA emission inventory guidebook 2016.



1.7.3 Results of uncertainty estimation

1.7.3.1 Qualitative assessment for all pollutants

A qualitative assessment was performed on sectoral level for all pollutants. The relevant sectors of each pollutant were classified in different quality groups from A to E (see Table 25) following the EMEP/EEA air pollutant emission inventory guidebook 2016 (EEA 2016). Table 24 presents a definition and default error ranges for each quality group.

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Table 25: Quality of emission estimates.

NFR Description SO2 NOx NMVOC NH3 CO Cd Hg Pb PAH Diox HCB PCB TSP PM10 PM2.5 1.A.1.a Public Electricity and

Heat Production A A D E A C C C C C C C B C C*

1.A.1.b Petroleum refining A A* E A C C C D D D D A B B 1.A.1.c Manufacture of Solid fuels

& Other Energy Ind. C B D E D C C C C D D C B B B

1.A.2 mobile

Other mobile in industry A B B C B C C C D D D D B B B

1.A.2 stat (l)

Manuf. Ind. and Constr. stationary LIQUID A B D E C C B C C E D D C C C

1.A.3.a Civil Aviation A B B C B B B B B B B 1.A.3.b.1 R.T., Passenger cars A B C D B B B C C D D D B B C 1.A.3.b.2 R.T., Light duty vehicles A B C D B B B C C D D D B B C 1.A.3.b.3 R.T., Heavy duty vehicles A B C D B B B C C D D D B B C 1.A.3.b.4 R.T., Mopeds &

Motorcycles A B C D B B B C D D D D B C C

1.A.3.b.5 R.T., Gasoline evaporation

C


B B B C C C C


C C C C

1.A.3.c Railways A B B C B B B C D D D D B B B 1.A.3.d Navigation A B B C B B B C D D D D B B B 1.A.3.e Other transportation C A* D E C C C C C D D C C C 1.A.4.a Commercial/ Institut. A B C* C C C C C D D D E C C C* 1.A.4.b Residential A B C* C C C C C D D D E C C C* 1.A.4.c Agriculture/Forestry/

Fisheries A C* C* C C C C C D D D E C C C*

1.A.5 Other B C C D C C C C D D D D C C C 1.B FUGITIVE EMISSIONS A A C C D D D 2.A MINERAL PRODUCTS D D D 2.B CHEMICAL INDUSTRY B B A A D A A B D A A A

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NFR Description SO2 NOx NMVOC NH3 CO Cd Hg Pb PAH Diox HCB PCB TSP PM10 PM2.5 2.C METAL PRODUCTION C B C B B B C C C C C B B B 2.D. NON ENERGY

PRODUCTS FROM FUELS /SOLVENT USE

B* B B B B B B

2.G Other product manufacture and use

C C C B D D D D D D C C C

2.H Other Processes B B B E E E D D D 2.I Wood Processing B B B 3.B.1 Cattle C C A D D D 3.B.2 Sheep C C B D D D 3.B.3 Swine C C A D D D 3.B.4.d Goats C C B D D D 3.B.4.e Horses C C B D D D 3.B.4.g Poultry C C B D D D 3.B.4.h Other animals C C B D D D 3.D Agricultural Soils C C/E B C D D D 3.F Field burning of

agricultural residues C C C C C C C C C C C C C C

5.A Solid waste disposal on land

B* B* C B B B D D D

5.B Biological treatment of waste

C

5.C Incineration and open burning of waste

D D C C C B B B C C C C D D D

5.D Wastewater treatment C 5.E Other waste C C C C D D D

Abbreviations: see Table 24 *value for calculation lies within quality rating, but is based on expert judgement and therefore no arithmetic mean value has been applied.



1.7.3.2 Quantitative uncertainty assessment

The quantitative uncertainty assessment was performed with the Tier 1 methods according to (EEA 2016) for the air pollutants SO2, NOx, NMVOC, NH3, CO, Cd, Hg, Pb, PAH, DIOX, HCB, PCB, TSP, PM10 and PM2.5 in the year 2018 and the respective level and trend uncertainties. Basis for this assessment is the qualitative rating as presented in Table 25.

The results of the uncertainty analysis are indicated in the following tables.

Table 26: Result of overall uncertainty estimation for the main pollutants (SO2, NOx, NMVOC, NH3,, CO), heavy metals and POPs (Cd, Hg, Pb, PAH, DIOX, HCB and PCB) and PMs (TSP, PM10 and PM2.5).

Pollutant Unit Emissions 2018 Level uncertainty 2018 [%]

Trend uncertainty 2018 [%]

SO2 [kt] 11.8 6.6 1.2

NOx [kt] 150.9 18.6 4.7

NMVOC [kt] 107.2 37.6 10.1

NH3 [kt] 64.6 21.5 6.0

CO [kt] 490.1 68.5 11.3

Cd [t] 1.1 41.0 10.2

Hg [t] 1.0 30.7 5.5

Pb [t] 19.3 46.9 7.6

PAH [t] 6.8 148.3 16.6

DIOX [g] 34.4 105.2 15.3

HCB [kg] 35.6 139.5 12.0

PCB [kg] 32.1 118.6 73.7

TSP [kt] 38.3 73.6 22.8

PM10 [kt] 26.4 61.8 17.2

PM2.5 [kt] 14.3 31.5 8.8

A more detailed presentation of the uncertainties on sectoral level per pollutant is given in the following tables below.

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Table 27: Uncertainty estimation of SO2 emissions 1990 and 2018.

NRF sector PollutantBase year emissions

Year t emissions

Activity data uncertainty

(1)

Emission factor

uncertainty (1)

Combined uncertainty

Contribution to variance by

category in year x

Type A sensitivity

Type B sensitivity

Uncertainty in trend in national emissions

introduced by emission factor /

estimation parameter uncertainty (2)


introduced by activity data

uncertainty (3)

Uncertainty introduced into the

trend in total national emissions

kt kt % % % % % % % % %

SO2 Input data Input datainput data

Note Ainput data

Note A

*

Note BI·F

Note C Note D K2 + L2

1 A 1 a SO2 11.8 1.0 8.0 20.0 21.54 3.06 -0.01 0.01 -0.25 0.15 0.081 A 1 b SO2 2.3 0.7 1.0 10.0 10.05 0.32 0.00 0.01 0.04 0.01 0.001 A 1 c SO2 0.0 0.0 2.0 125.0 125.02 0.00 0.00 0.00 0.00 0.00 0.001 A 2 a SO2 6.7 4.3 5.0 10.0 11.18 16.36 0.04 0.06 0.43 0.41 0.351 A 2 b SO2 0.2 0.1 5.0 20.0 20.62 0.02 0.00 0.00 0.02 0.01 0.001 A 2 c SO2 0.7 0.3 5.0 20.0 20.62 0.23 0.00 0.00 0.05 0.03 0.001 A 2 d SO2 4.3 0.8 10.0 20.0 22.36 2.37 0.00 0.01 0.03 0.16 0.031 A 2 e SO2 1.6 0.1 5.0 20.0 20.62 0.04 0.00 0.00 -0.04 0.01 0.001 A 2 f SO2 2.2 0.9 5.0 20.0 20.62 2.52 0.01 0.01 0.15 0.09 0.031 A 2 g 7 SO2 0.2 0.0 1.0 20.0 20.02 0.00 0.00 0.00 -0.01 0.00 0.001 A 2 g 8 SO2 1.9 1.4 10.0 20.0 22.36 6.61 0.01 0.02 0.29 0.26 0.151 A 3 a SO2 0.0 0.1 3.0 20.0 20.22 0.03 0.00 0.00 0.02 0.01 0.001 A 3 b 1 SO2 1.5 0.1 3.1 20.0 20.24 0.02 0.00 0.00 -0.04 0.00 0.001 A 3 b 2 SO2 0.7 0.0 3.1 20.0 20.24 0.00 0.00 0.00 -0.03 0.00 0.001 A 3 b 3 SO2 2.6 0.0 3.1 20.0 20.24 0.01 0.00 0.00 -0.10 0.00 0.011 A 3 b 4 SO2 0.0 0.0 3.1 20.0 20.24 0.00 0.00 0.00 0.00 0.00 0.001 A 3 c SO2 0.3 0.0 3.0 20.0 20.22 0.00 0.00 0.00 0.00 0.00 0.001 A 3 d SO2 0.0 0.0 3.0 20.0 20.22 0.00 0.00 0.00 0.00 0.00 0.001 A 3 e SO2 0.0 0.0 2.0 125.0 125.02 0.00 0.00 0.00 0.01 0.00 0.001 A 4 a SO2 4.9 0.1 5.0 20.0 20.62 0.02 -0.01 0.00 -0.19 0.01 0.041 A 4 b SO2 25.9 1.2 15.0 20.0 25.00 7.03 -0.04 0.02 -0.78 0.36 0.741 A 4 c SO2 1.8 0.1 5.0 20.0 20.62 0.03 0.00 0.00 -0.05 0.01 0.001 A 5 b SO2 0.0 0.0 1.0 40.0 40.01 0.00 0.00 0.00 0.01 0.00 0.001 B 2 b SO2 2.0 0.0 5.0 20.0 20.62 0.00 0.00 0.00 -0.08 0.00 0.012 B-10 SO2 1.6 0.4 2.0 40.0 40.05 1.55 0.00 0.00 0.06 0.01 0.002 C 1 SO2 0.3 0.1 0.5 125.0 125.00 0.29 0.00 0.00 0.02 0.00 0.002 C 7 SO2 0.1 0.1 5.0 125.0 125.10 2.52 0.00 0.00 0.22 0.01 0.052 G SO2 0.0 0.0 100.0 125.0 160.08 0.00 0.00 0.00 0.00 0.01 0.003 F SO2 0.0 0.0 100.0 125.0 160.08 0.00 0.00 0.00 0.00 0.00 0.005 C SO2 0.1 0.0 7.0 200.0 200.12 0.05 0.00 0.00 0.01 0.00 0.00Total 73.7 11.8 43.10 1.50

Total UncertaintiesUncertainty in total

inventory %: 6.57 Trend uncertainty %: 1.23

(E2 + F2)(G ∙ D)2∑(D2)

D∑C J ∙ E ∙ 2

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Table 28: Uncertainty estimation of NOx emissions 1990 and 2018.


Year t emissions


(1)

Emission factor

uncertainty (1)



category in year x

Type A sensitivity

Type B sensitivity






uncertainty (3)



kt kt % % % % % % % % %

NOX Input data Input datainput data

Note Ainput data

Note A

*

Note BI·F


1 A 1 a NOX 12.1 8.9 8.0 20.0 21.54 1.62 0.00 0.04 0.05 0.46 0.221 A 1 b NOX 4.3 1.1 1.0 10.0 10.05 0.01 -0.01 0.00 -0.09 0.01 0.011 A 1 c NOX 1.4 0.6 2.0 40.0 40.05 0.03 0.00 0.00 -0.06 0.01 0.001 A 2 a NOX 5.4 3.6 5.0 10.0 11.18 0.07 0.00 0.02 -0.01 0.12 0.011 A 2 b NOX 0.3 0.3 5.0 40.0 40.31 0.00 0.00 0.00 0.02 0.01 0.001 A 2 c NOX 1.7 1.4 5.0 40.0 40.31 0.14 0.00 0.01 0.04 0.05 0.001 A 2 d NOX 7.2 4.4 10.0 40.0 41.23 1.46 0.00 0.02 -0.10 0.29 0.091 A 2 e NOX 1.7 0.7 5.0 40.0 40.31 0.03 0.00 0.00 -0.10 0.02 0.011 A 2 f NOX 10.0 5.8 5.0 40.0 40.31 2.38 -0.01 0.03 -0.21 0.19 0.081 A 2 g 7 NOX 3.0 6.2 1.0 40.0 40.01 2.67 0.02 0.03 0.75 0.04 0.561 A 2 g 8 NOX 3.7 4.1 10.0 40.0 41.23 1.23 0.01 0.02 0.27 0.26 0.141 A 3 a NOX 0.4 1.6 3.0 40.0 40.11 0.19 0.01 0.01 0.25 0.03 0.061 A 3 b 1 NOX 60.2 54.1 3.1 40.0 40.12 207.21 0.06 0.25 2.26 1.09 6.311 A 3 b 2 NOX 7.3 10.0 3.1 40.0 40.12 7.06 0.02 0.05 0.91 0.20 0.861 A 3 b 3 NOX 49.0 16.3 3.1 40.0 40.12 18.79 -0.08 0.08 -3.25 0.33 10.701 A 3 b 4 NOX 0.1 0.2 3.1 40.0 40.12 0.00 0.00 0.00 0.03 0.00 0.001 A 3 c NOX 1.8 0.7 3.0 40.0 40.11 0.04 0.00 0.00 -0.10 0.01 0.011 A 3 d NOX 0.6 0.4 3.0 40.0 40.11 0.01 0.00 0.00 0.01 0.01 0.001 A 3 e NOX 0.6 0.3 2.0 10.0 10.20 0.00 0.00 0.00 0.00 0.00 0.001 A 4 a NOX 3.1 1.2 5.0 40.0 40.31 0.10 0.00 0.01 -0.18 0.04 0.031 A 4 b NOX 16.2 10.7 15.0 40.0 42.72 9.14 0.00 0.05 -0.11 1.04 1.101 A 4 c NOX 10.5 7.0 5.0 100.0 100.12 21.38 0.00 0.03 -0.15 0.23 0.081 A 5 b NOX 0.1 0.1 1.0 125.0 125.00 0.00 0.00 0.00 0.02 0.00 0.002 B 1 NOX IE 0.2 2.0 40.0 40.05 0.00 0.00 0.002 B 2 NOX IE 0.1 2.0 40.0 40.05 0.00 0.00 0.002 B-10 NOX 4.1 0.1 2.0 40.0 40.05 0.00 -0.01 0.00 -0.51 0.00 0.262 C 1 NOX 0.2 0.1 0.5 40.0 40.00 0.00 0.00 0.00 0.00 0.00 0.002 C 7 NOX 0.0 0.0 5.0 40.0 40.31 0.00 0.00 0.00 0.00 0.00 0.002 G NOX 0.0 0.0 100.0 125.0 160.08 0.00 0.00 0.00 0.00 0.02 0.002 H NOX NA NA 10.0 40.0 41.233 B 1 NOX 0.3 0.2 1.0 125.0 125.00 0.04 0.00 0.00 0.00 0.00 0.003 B 2 NOX 0.0 0.0 10.0 125.0 125.40 0.00 0.00 0.00 0.01 0.00 0.003 B 3 NOX 0.0 0.0 4.0 125.0 125.06 0.00 0.00 0.00 -0.01 0.00 0.003 B 4 NOX 0.2 0.3 10.0 125.0 125.40 0.05 0.00 0.00 0.08 0.02 0.013 D a NOX 11.4 10.2 5.0 125.0 125.10 71.23 0.01 0.05 1.30 0.33 1.803 F NOX 0.1 0.0 100.0 125.0 160.08 0.00 0.00 0.00 -0.01 0.01 0.005 C NOX 0.1 0.0 7.0 200.0 200.12 0.00 0.00 0.00 -0.05 0.00 0.00Total 217.2 150.9 344.89 22.35



(E2 + F2)D∑C J ∙ E ∙ 2

(G ∙ D)2∑(D2)

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Table 29: Uncertainty estimation of NMVOC emissions 1990 and 2018.


Year t emissions


(1)

Emission factor

uncertainty (1)



category in year x

Type A sensitivity

Type B sensitivity






uncertainty (3)



kt kt % % % % % % % % %

NMVOC Input data Input datainput data

Note Ainput data

Note A

* *

Note BI·F


1 A 1 a NMVOC 0.3 0.3 8.0 200.0 200.16 0.34 0.00 0.00 0.13 0.01 0.021 A 1 c NMVOC 0.0 0.0 2.0 200.0 200.01 0.00 0.00 0.00 0.00 0.00 0.001 A 2 a NMVOC 0.1 0.2 5.0 200.0 200.06 0.08 0.00 0.00 0.08 0.00 0.011 A 2 b NMVOC 0.0 0.0 5.0 200.0 200.06 0.00 0.00 0.00 0.00 0.00 0.001 A 2 c NMVOC 0.0 0.0 5.0 200.0 200.06 0.01 0.00 0.00 0.02 0.00 0.001 A 2 d NMVOC 0.7 0.3 10.0 200.0 200.25 0.23 0.00 0.00 0.01 0.01 0.001 A 2 e NMVOC 0.0 0.0 5.0 200.0 200.06 0.00 0.00 0.00 0.00 0.00 0.001 A 2 f NMVOC 0.2 0.2 5.0 200.0 200.06 0.19 0.00 0.00 0.09 0.01 0.011 A 2 g 7 NMVOC 0.5 0.2 1.0 40.0 40.01 0.01 0.00 0.00 0.00 0.00 0.001 A 2 g 8 NMVOC 0.0 0.1 10.0 40.0 41.23 0.00 0.00 0.00 0.01 0.01 0.001 A 3 a NMVOC 0.2 0.2 3.0 40.0 40.11 0.01 0.00 0.00 0.02 0.00 0.001 A 3 b 1 NMVOC 66.1 2.6 3.1 125.0 125.04 9.24 -0.06 0.01 -6.95 0.03 48.331 A 3 b 2 NMVOC 2.8 0.1 3.1 125.0 125.04 0.01 0.00 0.00 -0.30 0.00 0.091 A 3 b 3 NMVOC 5.1 0.4 3.1 125.0 125.04 0.19 0.00 0.00 -0.47 0.00 0.221 A 3 b 4 NMVOC 2.9 1.6 3.1 125.0 125.04 3.61 0.00 0.00 0.26 0.02 0.071 A 3 b 5 NMVOC 19.7 0.4 3.1 125.0 125.04 0.22 -0.02 0.00 -2.21 0.01 4.901 A 3 c NMVOC 0.4 0.1 3.0 40.0 40.11 0.00 0.00 0.00 -0.01 0.00 0.001 A 3 d NMVOC 0.6 0.2 3.0 40.0 40.11 0.01 0.00 0.00 0.00 0.00 0.001 A 3 e NMVOC 0.0 0.0 2.0 200.0 200.01 0.00 0.00 0.00 0.00 0.00 0.001 A 4 a NMVOC 1.3 0.6 5.0 70.0 70.18 0.15 0.00 0.00 0.03 0.01 0.001 A 4 b NMVOC 40.8 24.2 15.0 70.0 71.59 261.29 0.03 0.07 2.32 1.54 7.761 A 4 c NMVOC 5.7 2.6 5.0 100.0 100.12 5.88 0.00 0.01 0.23 0.05 0.061 A 5 b NMVOC 0.0 0.0 1.0 125.0 125.00 0.00 0.00 0.00 0.00 0.00 0.001 B 1 a NMVOC 2.9 NA 5.0 20.0 20.621 B 2 a NMVOC 11.4 1.8 0.5 20.0 20.01 0.11 -0.01 0.01 -0.11 0.00 0.011 B 2 b NMVOC 1.1 0.4 5.0 20.0 20.62 0.01 0.00 0.00 0.00 0.01 0.002 B-10 NMVOC 1.6 0.3 2.0 20.0 20.10 0.00 0.00 0.00 -0.02 0.00 0.002 C 1 NMVOC 0.3 0.3 0.5 125.0 125.00 0.09 0.00 0.00 0.06 0.00 0.002 C 7 NMVOC 0.2 0.2 5.0 125.0 125.10 0.06 0.00 0.00 0.05 0.00 0.002 D NMVOC 114.4 30.1 20.0 30.0 36.06 102.64 -0.02 0.09 -0.59 2.55 6.862 G NMVOC 0.1 0.1 100.0 125.0 160.08 0.01 0.00 0.00 0.01 0.03 0.002 H NMVOC 1.9 2.7 10.0 40.0 41.23 1.08 0.01 0.01 0.25 0.11 0.083 B 1 NMVOC 32.8 24.3 1.0 125.0 125.00 805.65 0.04 0.07 5.17 0.10 26.733 B 2 NMVOC 0.1 0.1 10.0 125.0 125.40 0.02 0.00 0.00 0.04 0.01 0.003 B 3 NMVOC 1.5 1.0 4.0 125.0 125.06 1.45 0.00 0.00 0.20 0.02 0.043 B 4 NMVOC 1.0 1.4 10.0 125.0 125.40 2.81 0.00 0.00 0.41 0.06 0.173 D a NMVOC 14.9 8.5 5.0 125.0 125.10 97.60 0.01 0.03 1.37 0.18 1.923 D e NMVOC 1.8 1.6 5.0 750.0 750.02 117.96 0.00 0.00 2.21 0.03 4.903 F NMVOC 0.1 0.0 100.0 125.0 160.08 0.00 0.00 0.00 0.00 0.00 0.005 A NMVOC 0.1 0.0 12.0 25.0 27.73 0.00 0.00 0.00 0.00 0.00 0.005 C NMVOC 0.0 0.0 7.0 125.0 125.20 0.00 0.00 0.00 0.00 0.00 0.005 D NMVOC 0.0 0.0 5.0 125.0 125.10 0.00 0.00 0.00 0.00 0.00 0.00Total 334.0 107.2 1.410.99 102.18

TotalUncertainty in total


(E2 + F2)D∑C

J ∙ E ∙ 2(G ∙ D)2∑(D2)

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Table 30: Uncertainty estimation of NH3 emissions 1990 and 2018.


Year t emissions


(1)

Emission factor

uncertainty (1)



category in year x

Type A sensitivity

Type B sensitivity






uncertainty (3)



kt kt % % % % % % % % %

NH3 Input data Input datainput data

Note Ainput data

Note A

*

Note BI·F


1 A 1 a NH3 0.1 0.3 8.0 750.0 750.04 15.24 0.00 0.01 2.67 0.06 7.121 A 1 b NH3 0.1 0.1 1.0 750.0 750.00 1.03 0.00 0.00 0.10 0.00 0.011 A 1 c NH3 0.0 0.0 2.0 750.0 750.00 0.00 0.00 0.00 -0.07 0.00 0.001 A 2 a NH3 0.0 0.0 5.0 750.0 750.02 0.06 0.00 0.00 0.08 0.00 0.011 A 2 b NH3 0.0 0.0 5.0 750.0 750.02 0.00 0.00 0.00 0.05 0.00 0.001 A 2 c NH3 0.0 0.0 5.0 750.0 750.02 0.16 0.00 0.00 0.08 0.00 0.011 A 2 d NH3 0.1 0.1 10.0 750.0 750.07 0.47 0.00 0.00 -0.21 0.01 0.041 A 2 e NH3 0.0 0.0 5.0 750.0 750.02 0.03 0.00 0.00 -0.08 0.00 0.011 A 2 f NH3 0.1 0.1 5.0 750.0 750.02 2.43 0.00 0.00 -0.15 0.02 0.021 A 2 g 7 NH3 0.0 0.0 1.0 125.0 125.00 0.00 0.00 0.00 0.00 0.00 0.001 A 2 g 8 NH3 0.1 0.1 10.0 125.0 125.40 0.06 0.00 0.00 0.15 0.03 0.021 A 3 a NH3 0.0 0.0 3.0 125.0 125.04 0.00 0.00 0.00 0.00 0.00 0.001 A 3 b 1 NH3 0.8 1.0 3.1 200.0 200.02 8.86 0.00 0.02 0.52 0.07 0.271 A 3 b 2 NH3 0.0 0.0 3.1 200.0 200.02 0.01 0.00 0.00 0.00 0.00 0.001 A 3 b 3 NH3 0.0 0.1 3.1 200.0 200.02 0.13 0.00 0.00 0.36 0.01 0.131 A 3 b 4 NH3 0.0 0.0 3.1 200.0 200.02 0.00 0.00 0.00 0.01 0.00 0.001 A 3 c NH3 0.0 0.0 3.0 125.0 125.04 0.00 0.00 0.00 0.00 0.00 0.001 A 3 d NH3 0.0 0.0 3.0 125.0 125.04 0.00 0.00 0.00 0.00 0.00 0.001 A 3 e NH3 0.0 0.0 2.0 750.0 750.00 0.02 0.00 0.00 0.08 0.00 0.011 A 4 a NH3 0.1 0.0 5.0 125.0 125.10 0.01 0.00 0.00 -0.06 0.01 0.001 A 4 b NH3 0.5 0.5 15.0 125.0 125.90 0.95 0.00 0.01 -0.09 0.17 0.041 A 4 c NH3 0.0 0.0 5.0 125.0 125.10 0.01 0.00 0.00 -0.01 0.00 0.001 A 5 b NH3 0.0 0.0 1.0 200.0 200.00 0.00 0.00 0.00 0.00 0.00 0.001 B 2 d NH3 NO 0.0 5.0 125.0 125.10 0.00 0.00 0.002 B 1 NH3 0.0 0.0 2.0 20.0 20.10 0.00 0.00 0.00 0.00 0.00 0.002 B 2 NH3 0.0 0.0 2.0 20.0 20.10 0.00 0.00 0.00 0.00 0.00 0.002 B-10 NH3 0.3 0.1 2.0 20.0 20.10 0.00 0.00 0.00 -0.07 0.00 0.002 G NH3 0.1 0.1 100.0 40.0 107.70 0.01 0.00 0.00 -0.01 0.13 0.023 B 1 NH3 13.9 17.9 1.0 20.0 20.02 30.82 0.05 0.29 1.09 0.41 1.363 B 2 NH3 0.7 1.0 10.0 40.0 41.23 0.39 0.00 0.02 0.13 0.22 0.073 B 3 NH3 8.5 5.7 4.0 20.0 20.40 3.23 -0.05 0.09 -1.03 0.52 1.333 B 4 NH3 2.9 4.5 10.0 40.0 41.23 8.37 0.02 0.07 0.94 1.04 1.973 D a NH3 33.0 31.2 5.0 40.0 40.31 379.24 -0.05 0.51 -2.13 3.58 17.333 F NH3 0.0 0.0 100.0 125.0 160.08 0.00 0.00 0.00 -0.06 0.02 0.005 A NH3 0.0 0.0 12.0 25.0 27.73 0.00 0.00 0.00 0.00 0.00 0.005 B NH3 0.4 1.6 20.0 125.0 126.59 9.82 0.02 0.03 2.47 0.73 6.655 C NH3 0.0 0.0 7.0 125.0 125.20 0.00 0.00 0.00 0.00 0.00 0.00Total 61.7 64.6 461.36 36.42



(E2 + F2)D∑C J ∙ E ∙ 2

(G ∙ D)2∑(D2)

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Table 31: Uncertainty estimation of CO emissions 1990 and 2018.


Year t emissions


(1)

Emission factor

uncertainty (1)



category in year x

Type A sensitivity

Type B sensitivity






uncertainty (3)



t t % % % % % % % % %

CO Input data Input datainput data

Note Ainput data

Note A

*

Note BI·F


1 A 1 a CO 1.4 4.0 8.0 20.0 21.54 0.03 0.00 0.00 0.05 0.04 0.001 A 1 b CO 4.7 0.3 1.0 20.0 20.02 0.00 0.00 0.00 -0.03 0.00 0.001 A 1 c CO 0.1 0.0 2.0 200.0 200.01 0.00 0.00 0.00 0.00 0.00 0.001 A 2 a CO 210.7 133.3 5.0 125.0 125.10 1.157.84 0.04 0.11 5.06 0.75 26.161 A 2 b CO 0.0 0.0 5.0 125.0 125.10 0.00 0.00 0.00 0.00 0.00 0.001 A 2 c CO 0.5 0.5 5.0 125.0 125.10 0.02 0.00 0.00 0.03 0.00 0.001 A 2 d CO 4.2 2.0 10.0 125.0 125.40 0.26 0.00 0.00 0.04 0.02 0.001 A 2 e CO 0.2 0.1 5.0 125.0 125.10 0.00 0.00 0.00 0.00 0.00 0.001 A 2 f CO 11.0 5.7 5.0 125.0 125.10 2.13 0.00 0.00 0.14 0.03 0.021 A 2 g 7 CO 3.8 4.1 1.0 40.0 40.01 0.11 0.00 0.00 0.08 0.00 0.011 A 2 g 8 CO 0.8 1.8 10.0 40.0 41.23 0.02 0.00 0.00 0.05 0.02 0.001 A 3 a CO 2.5 4.0 3.0 40.0 40.11 0.11 0.00 0.00 0.10 0.01 0.011 A 3 b 1 CO 467.1 44.9 3.1 40.0 40.12 13.53 -0.11 0.04 -4.41 0.16 19.481 A 3 b 2 CO 42.1 3.2 3.1 40.0 40.12 0.07 -0.01 0.00 -0.43 0.01 0.181 A 3 b 3 CO 12.4 7.6 3.1 40.0 40.12 0.39 0.00 0.01 0.09 0.03 0.011 A 3 b 4 CO 7.8 6.4 3.1 40.0 40.12 0.27 0.00 0.01 0.11 0.02 0.011 A 3 c CO 2.0 0.5 3.0 40.0 40.11 0.00 0.00 0.00 -0.01 0.00 0.001 A 3 d CO 3.2 2.0 3.0 40.0 40.11 0.03 0.00 0.00 0.02 0.01 0.001 A 3 e CO 0.0 0.1 2.0 125.0 125.02 0.00 0.00 0.00 0.01 0.00 0.001 A 4 a CO 11.8 3.9 5.0 125.0 125.10 1.01 0.00 0.00 -0.07 0.02 0.011 A 4 b CO 380.0 229.5 15.0 125.0 125.90 3.476.45 0.06 0.18 8.03 3.90 79.621 A 4 c CO 34.3 18.2 5.0 125.0 125.10 21.56 0.00 0.01 0.47 0.10 0.241 A 5 b CO 0.2 0.3 1.0 125.0 125.00 0.01 0.00 0.00 0.02 0.00 0.002 B 1 CO 0.1 0.1 2.0 200.0 200.01 0.00 0.00 0.00 0.00 0.00 0.002 B-10 CO 12.5 11.1 2.0 200.0 200.01 20.40 0.00 0.01 0.98 0.03 0.972 C 1 CO 23.2 2.0 0.5 40.0 40.00 0.03 -0.01 0.00 -0.23 0.00 0.052 C 7 CO 0.1 0.1 5.0 40.0 40.31 0.00 0.00 0.00 0.00 0.00 0.002 D CO 0.3 0.3 20.0 40.0 44.72 0.00 0.00 0.00 0.01 0.01 0.002 G CO 0.9 0.7 100.0 200.0 223.61 0.11 0.00 0.00 0.06 0.08 0.012 H CO NA NA 10.0 40.0 41.233 F CO 1.2 0.3 100.0 125.0 160.08 0.01 0.00 0.00 -0.01 0.04 0.005 A CO 10.3 2.9 12.0 125.0 125.57 0.57 0.00 0.00 -0.11 0.04 0.015 C CO 0.1 0.0 7.0 125.0 125.20 0.00 0.00 0.00 0.00 0.00 0.00Total 1249.4 490.1 4.694.94 126.80



(E2 + F2)(G ∙ D)2∑(D2)

D∑C J ∙ E ∙ 2

Austria’s Inform



Um

weltbundesam

t R

EP-0723, V

ienna 2020 79

Table 32: Uncertainty estimation of Cd emissions 1990 and 2018.


Year t emissions


(1)

Emission factor

uncertainty (1)



category in year x

Type A sensitivity

Type B sensitivity






uncertainty (3)



t t % % % % % % % % %

Cd Input data Input datainput data

Note Ainput data

Note A

*

Note BI·F


1 A 1 a Cd 0.2 0.1 8.0 125.0 125.26 217.64 0.01 0.08 1.25 0.86 2.291 A 1 b Cd 0.1 0.1 1.0 125.0 125.00 255.73 0.03 0.08 3.53 0.12 12.471 A 1 c Cd 0.0 0.0 2.0 125.0 125.02 0.00 0.00 0.00 0.00 0.00 0.001 A 2 a Cd 0.0 0.0 5.0 125.0 125.10 0.13 0.00 0.00 -0.05 0.01 0.001 A 2 b Cd 0.0 0.0 5.0 125.0 125.10 0.04 0.00 0.00 0.04 0.01 0.001 A 2 c Cd 0.0 0.0 5.0 125.0 125.10 2.06 0.00 0.01 -0.37 0.05 0.141 A 2 d Cd 0.2 0.1 10.0 125.0 125.40 254.91 0.03 0.08 3.34 1.16 12.511 A 2 e Cd 0.0 0.0 5.0 125.0 125.10 0.01 0.00 0.00 -0.03 0.00 0.001 A 2 f Cd 0.1 0.0 5.0 125.0 125.10 6.05 -0.02 0.01 -2.88 0.09 8.301 A 2 g 7 Cd 0.0 0.0 1.0 125.0 125.00 0.00 0.00 0.00 0.02 0.00 0.001 A 2 g 8 Cd 0.0 0.1 10.0 125.0 125.40 45.51 0.03 0.03 3.34 0.49 11.411 A 3 a Cd 0.0 0.0 3.0 40.0 40.11 0.00 0.00 0.00 0.00 0.00 0.001 A 3 b 1 Cd 0.0 0.0 3.1 40.0 40.12 0.02 0.00 0.00 0.05 0.01 0.001 A 3 b 2 Cd 0.0 0.0 3.1 40.0 40.12 0.00 0.00 0.00 0.01 0.00 0.001 A 3 b 3 Cd 0.0 0.0 3.1 40.0 40.12 0.00 0.00 0.00 0.03 0.00 0.001 A 3 b 4 Cd 0.0 0.0 3.1 40.0 40.12 0.00 0.00 0.00 0.00 0.00 0.001 A 3 b 6 Cd 0.0 0.0 3.1 40.0 40.12 0.62 0.01 0.01 0.33 0.06 0.111 A 3 c Cd 0.0 0.0 3.0 40.0 40.11 0.00 0.00 0.00 -0.01 0.00 0.001 A 3 d Cd 0.0 0.0 3.0 40.0 40.11 0.00 0.00 0.00 0.00 0.00 0.001 A 3 e Cd 0.0 0.0 2.0 40.0 40.05 0.00 0.00 0.00 0.00 0.00 0.001 A 4 a Cd 0.1 0.0 5.0 125.0 125.10 4.45 -0.01 0.01 -1.28 0.08 1.641 A 4 b Cd 0.3 0.2 15.0 125.0 125.90 613.49 0.01 0.13 1.52 2.70 9.571 A 4 c Cd 0.0 0.0 5.0 125.0 125.10 27.26 0.02 0.03 1.93 0.19 3.781 A 5 b Cd 0.0 0.0 1.0 125.0 125.00 0.00 0.00 0.00 0.00 0.00 0.002 B-10 Cd 0.0 0.0 2.0 20.0 20.10 0.00 0.00 0.00 0.00 0.00 0.002 C 1 Cd 0.5 0.2 0.5 40.0 40.00 54.28 -0.05 0.12 -1.95 0.08 3.792 C 5 Cd 0.1 0.0 10.0 40.0 41.23 0.03 -0.02 0.00 -0.93 0.04 0.862 C 7 Cd 0.0 0.0 5.0 40.0 40.31 0.00 0.00 0.00 -0.20 0.00 0.042 D Cd 0.0 0.0 20.0 40.0 44.72 0.00 0.00 0.00 0.00 0.00 0.002 G Cd 0.1 0.1 100.0 200.0 223.61 202.25 0.01 0.04 1.35 5.81 35.593 F Cd 0.0 0.0 100.0 125.0 160.08 0.05 0.00 0.00 -0.26 0.12 0.085 A Cd 0.0 0.0 12.0 40.0 41.76 0.00 0.00 0.00 -0.01 0.00 0.005 C Cd 0.1 0.0 7.0 40.0 40.61 0.00 -0.02 0.00 -0.84 0.00 0.715 E Cd 0.0 0.0 50.0 200.0 206.16 0.05 0.00 0.00 0.05 0.05 0.00Total 1.8 1.1 1.684.57 103.32



(E2 + F2)(G ∙ D)2∑(D2)

D∑C J ∙ E ∙ 2

Austria’s Inform



80 U

mw

eltbundesamt

REP

-0723, Vienna 2020

Table 33: Uncertainty estimation of Hg emissions 1990 and 2018.


Year t emissions


(1)

Emission factor

uncertainty (1)



category in year x

Type A sensitivity

Type B sensitivity






uncertainty (3)



t t % % % % % % % % %

Hg Input data Input datainput data

Note Ainput data

Note A

*

Note BI·F


1 A 1 a Hg 0.3 0.1 8.0 125.0 125.26 348.06 0.00 0.07 -0.57 0.75 0.881 A 1 b Hg 0.0 0.0 1.0 125.0 125.00 5.27 0.01 0.01 0.83 0.01 0.691 A 1 c Hg 0.0 0.0 2.0 125.0 125.02 0.00 0.00 0.00 0.00 0.00 0.001 A 2 a Hg 0.0 0.0 5.0 40.0 40.31 0.00 0.00 0.00 0.00 0.00 0.001 A 2 b Hg 0.0 0.0 5.0 40.0 40.31 0.00 0.00 0.00 0.00 0.00 0.001 A 2 c Hg 0.0 0.0 5.0 40.0 40.31 0.14 0.00 0.00 0.07 0.03 0.011 A 2 d Hg 0.1 0.1 10.0 40.0 41.23 13.12 0.02 0.04 1.00 0.55 1.291 A 2 e Hg 0.0 0.0 5.0 40.0 40.31 0.00 0.00 0.00 0.00 0.00 0.001 A 2 f Hg 0.7 0.2 5.0 40.0 40.31 48.50 -0.07 0.08 -2.67 0.54 7.411 A 2 g 7 Hg 0.0 0.0 1.0 125.0 125.00 0.00 0.00 0.00 0.01 0.00 0.001 A 2 g 8 Hg 0.0 0.0 10.0 125.0 125.40 14.21 0.01 0.01 1.43 0.19 2.091 A 3 a Hg 0.0 0.0 3.0 40.0 40.11 0.00 0.00 0.00 0.00 0.00 0.001 A 3 b 1 Hg 0.0 0.0 3.1 40.0 40.12 0.00 0.00 0.00 0.02 0.00 0.001 A 3 b 2 Hg 0.0 0.0 3.1 40.0 40.12 0.00 0.00 0.00 0.00 0.00 0.001 A 3 b 3 Hg 0.0 0.0 3.1 40.0 40.12 0.00 0.00 0.00 0.01 0.00 0.001 A 3 b 4 Hg 0.0 0.0 3.1 40.0 40.12 0.00 0.00 0.00 0.00 0.00 0.001 A 3 c Hg 0.0 0.0 3.0 40.0 40.11 0.00 0.00 0.00 -0.01 0.00 0.001 A 3 d Hg 0.0 0.0 3.0 40.0 40.11 0.00 0.00 0.00 0.00 0.00 0.001 A 3 e Hg 0.0 0.0 2.0 40.0 40.05 0.00 0.00 0.00 0.02 0.00 0.001 A 4 a Hg 0.0 0.0 5.0 125.0 125.10 0.90 0.00 0.00 -0.18 0.02 0.031 A 4 b Hg 0.4 0.1 15.0 125.0 125.90 355.63 -0.01 0.07 -1.68 1.41 4.811 A 4 c Hg 0.0 0.0 5.0 125.0 125.10 2.91 0.00 0.01 0.41 0.04 0.171 A 5 b Hg 0.0 0.0 1.0 125.0 125.00 0.00 0.00 0.00 0.00 0.00 0.001 B 2 d Hg NO 0.0 5.0 0.0 5.00 0.00 0.00 0.002 B-10 Hg 0.3 0.0 2.0 20.0 20.10 0.00 -0.06 0.00 -1.10 0.00 1.222 C 1 Hg 0.3 0.3 0.5 40.0 40.00 150.29 0.08 0.14 3.32 0.10 11.022 C 7 Hg 0.0 0.0 5.0 40.0 40.31 0.11 0.00 0.00 0.10 0.03 0.012 G Hg 0.0 0.0 100.0 200.0 223.61 0.00 0.00 0.00 0.00 0.00 0.003 F Hg 0.0 0.0 100.0 125.0 160.08 0.00 0.00 0.00 -0.02 0.02 0.005 A Hg 0.0 0.0 12.0 40.0 41.76 0.00 0.00 0.00 0.00 0.00 0.005 C Hg 0.1 0.0 7.0 40.0 40.61 2.59 0.01 0.02 0.26 0.17 0.105 E Hg 0.0 0.0 50.0 200.0 206.16 0.06 0.00 0.00 0.06 0.04 0.00Total 2.2 1.0 941.80 29.75



(E2 + F2)(G ∙ D)2∑(D2)

D∑C J ∙ E ∙ 2

Austria’s Inform



Um

weltbundesam

t R

EP-0723, V

ienna 2020 81

Table 34: Uncertainty estimation of Pb emissions 1990 and 2018.


Year t emissions


(1)

Emission factor

uncertainty (1)



category in year x

Type A sensitivity

Type B sensitivity






uncertainty (3)



t t % % % % % % % % %

Pb Input data Input datainput data

Note Ainput data

Note A

*

Note BI·F


1 A 1 a Pb 1.3 1.9 8.0 125.0 125.26 153.70 0.01 0.01 0.97 0.09 0.951 A 1 b Pb 0.2 0.5 1.0 125.0 125.00 9.30 0.00 0.00 0.24 0.00 0.061 A 1 c Pb 0.0 0.0 2.0 125.0 125.02 0.00 0.00 0.00 0.00 0.00 0.001 A 2 a Pb 0.3 0.2 5.0 125.0 125.10 1.01 0.00 0.00 0.07 0.00 0.011 A 2 b Pb 0.0 0.0 5.0 125.0 125.10 0.00 0.00 0.00 0.00 0.00 0.001 A 2 c Pb 0.2 0.3 5.0 125.0 125.10 2.98 0.00 0.00 0.13 0.01 0.021 A 2 d Pb 0.6 1.0 10.0 125.0 125.40 40.40 0.00 0.00 0.50 0.06 0.251 A 2 e Pb 0.0 0.0 5.0 125.0 125.10 0.00 0.00 0.00 0.00 0.00 0.001 A 2 f Pb 4.3 0.3 5.0 125.0 125.10 3.85 0.00 0.00 -0.03 0.01 0.001 A 2 g 7 Pb 0.1 0.0 1.0 125.0 125.00 0.00 0.00 0.00 0.00 0.00 0.001 A 2 g 8 Pb 0.1 0.5 10.0 125.0 125.40 12.14 0.00 0.00 0.28 0.03 0.081 A 3 a Pb 1.6 0.0 3.0 40.0 40.11 0.00 0.00 0.00 -0.02 0.00 0.001 A 3 b 1 Pb 162.3 0.0 3.1 125.0 125.04 0.00 -0.06 0.00 -7.18 0.00 51.531 A 3 b 2 Pb 6.9 0.0 3.1 125.0 125.04 0.00 0.00 0.00 -0.31 0.00 0.091 A 3 b 3 Pb 4.1 0.0 3.1 125.0 125.04 0.00 0.00 0.00 -0.18 0.00 0.031 A 3 b 4 Pb 1.7 0.0 3.1 125.0 125.04 0.00 0.00 0.00 -0.07 0.00 0.011 A 3 b 6 Pb 2.7 4.8 3.1 40.0 40.12 99.91 0.02 0.02 0.79 0.09 0.631 A 3 c Pb 0.0 0.0 3.0 125.0 125.04 0.00 0.00 0.00 0.00 0.00 0.001 A 3 d Pb 0.3 0.0 3.0 125.0 125.04 0.00 0.00 0.00 -0.01 0.00 0.001 A 3 e Pb 0.0 0.0 2.0 40.0 40.05 0.00 0.00 0.00 0.00 0.00 0.001 A 4 a Pb 0.4 0.1 5.0 125.0 125.10 0.79 0.00 0.00 0.06 0.00 0.001 A 4 b Pb 6.0 1.8 15.0 125.0 125.90 130.94 0.01 0.01 0.67 0.16 0.481 A 4 c Pb 1.0 0.2 5.0 125.0 125.10 1.02 0.00 0.00 0.04 0.00 0.001 A 5 b Pb 0.0 0.0 1.0 125.0 125.00 0.00 0.00 0.00 0.00 0.00 0.002 B-10 Pb 0.0 0.0 2.0 40.0 40.05 0.00 0.00 0.00 0.00 0.00 0.002 C 1 Pb 32.1 6.2 0.5 125.0 125.00 1.639.99 0.02 0.03 1.92 0.02 3.702 C 3 Pb 0.0 0.1 2.0 125.0 125.02 0.37 0.00 0.00 0.05 0.00 0.002 C 5 Pb 3.5 0.6 10.0 125.0 125.40 14.54 0.00 0.00 0.16 0.04 0.032 C 7 Pb 0.5 0.0 5.0 125.0 125.10 0.00 0.00 0.00 -0.02 0.00 0.002 D Pb 0.0 0.0 20.0 40.0 44.72 0.00 0.00 0.00 0.00 0.00 0.002 G Pb 1.2 0.8 100.0 200.0 223.61 93.26 0.00 0.00 0.63 0.51 0.653 F Pb 0.0 0.0 100.0 125.0 160.08 0.00 0.00 0.00 0.00 0.00 0.005 A Pb 0.0 0.0 12.0 40.0 41.76 0.00 0.00 0.00 0.00 0.00 0.005 C Pb 1.0 0.0 7.0 40.0 40.61 0.00 0.00 0.00 -0.01 0.00 0.005 E Pb 0.0 0.0 50.0 200.0 206.16 0.00 0.00 0.00 0.00 0.00 0.00Total 232.4 19.3 2.204.22 58.52



(E2 + F2)(G ∙ D)2∑(D2)

D∑C

J ∙ E ∙ 2

Austria’s Inform



82 U

mw

eltbundesamt

REP

-0723, Vienna 2020

Table 35: Uncertainty estimation of PAH emissions 1990 and 2018.


Year t emissions


(1)

Emission factor

uncertainty (1)



category in year x

Type A sensitivity

Type B sensitivity






uncertainty (3)



t t % % % % % % % % %

PAH Input data Input datainput data

Note Ainput data

Note A

*

Note BI·F


1 A 1 a PAH 0.0 0.0 8.0 125.0 125.26 0.17 0.00 0.00 0.14 0.01 0.021 A 1 b PAH 0.0 0.0 1.0 200.0 200.00 0.01 0.00 0.00 0.03 0.00 0.001 A 1 c PAH 0.0 0.0 2.0 125.0 125.02 0.00 0.00 0.00 0.00 0.00 0.001 A 2 a PAH 0.0 0.0 5.0 125.0 125.10 0.00 0.00 0.00 0.00 0.00 0.001 A 2 b PAH 0.0 0.0 5.0 125.0 125.10 0.00 0.00 0.00 0.00 0.00 0.001 A 2 c PAH 0.0 0.0 5.0 125.0 125.10 0.14 0.00 0.00 0.09 0.01 0.011 A 2 d PAH 0.0 0.0 10.0 125.0 125.40 0.00 0.00 0.00 0.02 0.00 0.001 A 2 e PAH 0.0 0.0 5.0 125.0 125.10 0.00 0.00 0.00 0.01 0.00 0.001 A 2 f PAH 0.0 0.0 5.0 125.0 125.10 0.03 0.00 0.00 0.05 0.00 0.001 A 2 g 7 PAH 0.0 0.1 1.0 200.0 200.00 10.76 0.01 0.01 1.09 0.01 1.181 A 2 g 8 PAH 0.0 0.1 10.0 200.0 200.25 4.19 0.00 0.00 0.68 0.05 0.461 A 3 b 1 PAH 0.2 0.2 3.1 125.0 125.04 8.88 0.01 0.01 0.67 0.04 0.451 A 3 b 2 PAH 0.0 0.0 3.1 125.0 125.04 0.11 0.00 0.00 0.02 0.00 0.001 A 3 b 3 PAH 0.0 0.1 3.1 125.0 125.04 6.25 0.01 0.01 0.78 0.03 0.611 A 3 b 4 PAH 0.0 0.0 3.1 200.0 200.02 0.00 0.00 0.00 0.02 0.00 0.001 A 3 b 6 PAH 0.0 0.0 3.1 125.0 125.04 0.02 0.00 0.00 0.04 0.00 0.001 A 3 c PAH 0.0 0.0 3.0 200.0 200.02 0.06 0.00 0.00 0.01 0.00 0.001 A 3 d PAH 0.0 0.0 3.0 200.0 200.02 0.02 0.00 0.00 0.03 0.00 0.001 A 3 e PAH 0.0 0.0 2.0 40.0 40.05 0.00 0.00 0.00 0.00 0.00 0.001 A 4 a PAH 0.3 0.1 5.0 200.0 200.06 5.55 0.00 0.00 -0.28 0.03 0.081 A 4 b PAH 10.6 4.9 15.0 200.0 200.56 21.132.07 0.06 0.26 11.83 5.49 170.061 A 4 c PAH 0.5 1.0 5.0 200.0 200.06 787.84 0.04 0.05 8.05 0.35 64.871 A 5 b PAH 0.0 0.0 1.0 200.0 200.00 0.00 0.00 0.00 0.00 0.00 0.002 C 1 PAH 0.3 0.2 0.5 125.0 125.00 10.15 0.00 0.01 0.32 0.01 0.102 C 3 PAH 6.1 NE 2.0 125.0 125.022 D PAH 0.2 NA 20.0 40.0 44.722 G PAH 0.0 0.0 100.0 200.0 223.61 0.01 0.00 0.00 0.02 0.02 0.002 H PAH 0.5 0.0 10.0 750.0 750.07 16.67 -0.01 0.00 -6.21 0.03 38.583 F PAH 0.1 0.0 100.0 125.0 160.08 0.96 0.00 0.00 0.08 0.31 0.105 C PAH 0.0 0.0 7.0 125.0 125.20 0.00 0.00 0.00 0.00 0.00 0.00Total 19.0 6.8 21.983.90 276.53



(E2 + F2)(G ∙ D)2∑(D2)

D∑C J ∙ E ∙ 2

Austria’s Inform



Um

weltbundesam

t R

EP-0723, V

ienna 2020 83

Table 36: Uncertainty estimation of DIOX emissions 1990 and 2018.


Year t emissions


(1)

Emission factor

uncertainty (1)



category in year x

Type A sensitivity

Type B sensitivity






uncertainty (3)



g g % % % % % % % % %

DIOX Input data Input datainput data

Note Ainput data

Note A

*

Note BI·F


1 A 1 a DIOX 12.1 1.3 8.0 125.0 125.26 23.22 -0.02 0.01 -2.00 0.12 4.021 A 1 b DIOX 0.0 0.0 1.0 200.0 200.00 0.01 0.00 0.00 0.02 0.00 0.001 A 1 c DIOX 0.0 0.0 2.0 200.0 200.01 0.00 0.00 0.00 0.00 0.00 0.001 A 2 a DIOX 0.0 0.0 5.0 750.0 750.02 0.31 0.00 0.00 0.10 0.00 0.011 A 2 b DIOX 0.0 0.0 5.0 750.0 750.02 0.70 0.00 0.00 0.20 0.00 0.041 A 2 c DIOX 0.4 0.5 5.0 750.0 750.02 127.25 0.00 0.00 2.38 0.03 5.681 A 2 d DIOX 0.5 0.6 10.0 750.0 750.07 183.90 0.00 0.00 2.91 0.07 8.461 A 2 e DIOX 0.0 0.0 5.0 750.0 750.02 0.95 0.00 0.00 0.22 0.00 0.051 A 2 f DIOX 0.3 0.5 5.0 750.0 750.02 108.10 0.00 0.00 2.38 0.03 5.641 A 2 g 7 DIOX 0.0 0.1 1.0 200.0 200.00 0.62 0.00 0.00 0.21 0.00 0.041 A 2 g 8 DIOX 0.3 1.8 10.0 200.0 200.25 104.79 0.01 0.01 2.66 0.20 7.101 A 3 b 1 DIOX 3.6 0.6 3.1 200.0 200.02 14.01 0.00 0.01 -0.56 0.02 0.321 A 3 b 2 DIOX 0.2 0.1 3.1 200.0 200.02 0.31 0.00 0.00 0.08 0.00 0.011 A 3 b 3 DIOX 0.3 0.8 3.1 200.0 200.02 21.37 0.01 0.01 1.13 0.03 1.271 A 3 b 4 DIOX 0.0 0.0 3.1 200.0 200.02 0.01 0.00 0.00 0.02 0.00 0.001 A 3 c DIOX 0.0 0.0 3.0 200.0 200.02 0.00 0.00 0.00 0.00 0.00 0.001 A 3 d DIOX 0.0 0.0 3.0 200.0 200.02 0.00 0.00 0.00 0.01 0.00 0.001 A 3 e DIOX 0.0 0.0 2.0 200.0 200.01 0.00 0.00 0.00 0.00 0.00 0.001 A 4 a DIOX 1.7 0.5 5.0 200.0 200.06 8.89 0.00 0.00 0.05 0.03 0.001 A 4 b DIOX 40.6 17.2 15.0 200.0 200.56 10.025.30 0.05 0.14 9.59 2.91 100.391 A 4 c DIOX 1.5 1.4 5.0 200.0 200.06 62.70 0.01 0.01 1.50 0.08 2.271 A 5 b DIOX 0.0 0.0 1.0 200.0 200.00 0.00 0.00 0.00 0.00 0.00 0.002 C 1 DIOX 37.2 2.5 0.5 125.0 125.00 82.21 -0.06 0.02 -7.70 0.01 59.302 C 3 DIOX 2.4 3.3 2.0 125.0 125.02 143.42 0.02 0.03 2.63 0.07 6.932 C 5 DIOX 0.1 0.1 10.0 125.0 125.40 0.07 0.00 0.00 0.05 0.01 0.002 C 7 DIOX 0.3 0.4 5.0 125.0 125.10 2.12 0.00 0.00 0.31 0.02 0.102 D DIOX 1.1 NA 20.0 40.0 44.722 G DIOX 0.0 0.0 100.0 200.0 223.61 0.00 0.00 0.00 0.00 0.00 0.002 H DIOX 1.8 0.1 10.0 750.0 750.07 8.15 0.00 0.00 -2.16 0.01 4.673 F DIOX 0.2 0.1 100.0 125.0 160.08 0.06 0.00 0.00 0.00 0.06 0.005 C DIOX 18.2 0.3 7.0 125.0 125.20 1.31 -0.04 0.00 -4.67 0.02 21.845 E DIOX 2.1 2.1 50.0 200.0 206.16 152.05 0.01 0.02 2.37 1.16 6.96Total 125.2 34.4 11.071.84 235.11



(E2 + F2)(G ∙ D)2∑(D2)

D∑C J ∙ E ∙ 2

Austria’s Inform



84 U

mw

eltbundesamt

REP

-0723, Vienna 2020

Table 37: Uncertainty estimation of HCB emissions 1990 and 2018.


Year t emissions


(1)

Emission factor

uncertainty (1)



category in year x

Type A sensitivity

Type B sensitivity






uncertainty (3)



kg kg % % % % % % % % %

HCB Input data Input datainput data

Note Ainput data

Note A

*

Note BI·F


1 A 1 a HCB 0.3 0.5 8.0 125.0 125.26 2.94 0.00 0.01 0.55 0.06 0.301 A 1 b HCB 0.0 0.0 1.0 200.0 200.00 0.00 0.00 0.00 0.00 0.00 0.001 A 1 c HCB 0.0 0.0 2.0 200.0 200.01 0.00 0.00 0.00 0.00 0.00 0.001 A 2 a HCB 0.0 0.0 5.0 200.0 200.06 0.00 0.00 0.00 0.00 0.00 0.001 A 2 b HCB 0.0 0.0 5.0 200.0 200.06 0.00 0.00 0.00 0.00 0.00 0.001 A 2 c HCB 0.1 0.1 5.0 200.0 200.06 0.19 0.00 0.00 0.12 0.01 0.011 A 2 d HCB 0.1 0.1 10.0 200.0 200.25 0.49 0.00 0.00 0.19 0.02 0.041 A 2 e HCB 0.0 0.0 5.0 200.0 200.06 0.00 0.00 0.00 0.01 0.00 0.001 A 2 f HCB 0.1 0.1 5.0 200.0 200.06 0.21 0.00 0.00 0.13 0.01 0.021 A 2 g 7 HCB 0.0 0.0 1.0 200.0 200.00 0.02 0.00 0.00 0.06 0.00 0.001 A 2 g 8 HCB 0.1 0.3 10.0 200.0 200.25 2.39 0.00 0.00 0.59 0.05 0.351 A 3 b 1 HCB 0.7 0.1 3.1 200.0 200.02 0.52 0.00 0.00 -0.41 0.01 0.161 A 3 b 2 HCB 0.0 0.0 3.1 200.0 200.02 0.01 0.00 0.00 0.01 0.00 0.001 A 3 b 3 HCB 0.1 0.2 3.1 200.0 200.02 0.80 0.00 0.00 0.31 0.01 0.091 A 3 b 4 HCB 0.0 0.0 3.1 200.0 200.02 0.00 0.00 0.00 0.01 0.00 0.001 A 3 c HCB 0.0 0.0 3.0 200.0 200.02 0.00 0.00 0.00 0.00 0.00 0.001 A 3 d HCB 0.0 0.0 3.0 200.0 200.02 0.00 0.00 0.00 0.00 0.00 0.001 A 3 e HCB 0.0 0.0 2.0 200.0 200.01 0.00 0.00 0.00 0.00 0.00 0.001 A 4 a HCB 1.6 0.4 5.0 200.0 200.06 6.35 0.00 0.01 -0.46 0.04 0.211 A 4 b HCB 50.0 24.5 15.0 200.0 200.56 19.051.74 0.04 0.29 8.52 6.08 109.631 A 4 c HCB 1.9 2.3 5.0 200.0 200.06 169.81 0.02 0.03 3.58 0.19 12.891 A 5 b HCB 0.0 0.0 1.0 200.0 200.00 0.00 0.00 0.00 0.00 0.00 0.002 B-10 HCB 1.3 NA 2.0 200.0 200.012 C 1 HCB 8.1 3.5 0.5 125.0 125.00 153.98 0.00 0.04 0.24 0.03 0.062 C 3 HCB 1.2 1.6 2.0 125.0 125.02 33.45 0.01 0.02 1.68 0.05 2.822 C 7 HCB 0.1 0.1 5.0 125.0 125.10 0.26 0.00 0.00 0.15 0.01 0.022 D HCB 9.1 NA 20.0 40.0 44.722 H HCB 0.4 0.0 10.0 750.0 750.07 0.30 0.00 0.00 -1.08 0.00 1.163 D f HCB 10.1 1.5 0.0 125.0 125.00 27.97 -0.03 0.02 -3.95 0.00 15.643 F HCB 0.0 0.0 100.0 125.0 160.08 0.00 0.00 0.00 -0.01 0.02 0.005 C HCB 0.4 0.1 7.0 125.0 125.20 0.05 0.00 0.00 -0.15 0.01 0.02Total 85.5 35.6 19.451.49 143.44



(E2 + F2)(G ∙ D)2∑(D2)

D∑C J ∙ E ∙ 2

Austria’s Inform



Um

weltbundesam

t R

EP-0723, V

ienna 2020 85

Table 38: Uncertainty estimation of PCB emissions 1990 and 2018.


Year t emissions


(1)

Emission factor

uncertainty (1)



category in year x

Type A sensitivity

Type B sensitivity






uncertainty (3)



kg kg % % % % % % % % %

PCB Input data Input datainput data

Note Ainput data

Note A

*

Note BI·F


1 A 1 a PCB 1.2 0.1 8.0 125.0 125.26 0.04 -0.02 0.00 -1.96 0.01 3.831 A 1 b PCB 0.0 0.0 1.0 200.0 200.00 0.00 0.00 0.00 0.00 0.00 0.001 A 1 c PCB 0.0 0.0 2.0 200.0 200.01 0.00 0.00 0.00 0.00 0.00 0.001 A 2 a PCB 0.1 0.0 5.0 200.0 200.06 0.02 0.00 0.00 -0.15 0.00 0.021 A 2 b PCB 0.0 0.0 5.0 200.0 200.06 0.01 0.00 0.00 -0.04 0.00 0.001 A 2 c PCB 0.2 0.2 5.0 200.0 200.06 2.15 0.00 0.00 0.40 0.04 0.161 A 2 d PCB 1.5 0.7 10.0 200.0 200.25 20.07 -0.01 0.02 -1.26 0.21 1.631 A 2 e PCB 0.2 0.0 5.0 200.0 200.06 0.02 0.00 0.00 -0.33 0.00 0.111 A 2 f PCB 0.5 0.4 5.0 200.0 200.06 7.71 0.00 0.01 0.51 0.07 0.271 A 2 g 7 PCB 0.0 0.0 1.0 200.0 200.00 0.00 0.00 0.00 0.00 0.00 0.001 A 2 g 8 PCB 0.2 0.0 10.0 200.0 200.25 0.01 0.00 0.00 -0.49 0.00 0.241 A 3 b 1 PCB 0.0 0.0 3.1 200.0 200.02 0.00 0.00 0.00 0.00 0.00 0.001 A 3 b 2 PCB 0.0 0.0 3.1 200.0 200.02 0.00 0.00 0.00 0.00 0.00 0.001 A 3 b 3 PCB 0.0 0.0 3.1 200.0 200.02 0.00 0.00 0.00 0.00 0.00 0.001 A 3 b 4 PCB 0.0 0.0 3.1 200.0 200.02 0.00 0.00 0.00 0.00 0.00 0.001 A 3 c PCB 0.0 0.0 3.0 200.0 200.02 0.00 0.00 0.00 0.00 0.00 0.001 A 3 d PCB 0.0 0.0 3.0 200.0 200.02 0.00 0.00 0.00 0.00 0.00 0.001 A 3 e PCB 0.0 0.0 2.0 200.0 200.01 0.00 0.00 0.00 0.00 0.00 0.001 A 4 a PCB 0.3 0.0 5.0 750.0 750.02 0.00 0.00 0.00 -3.26 0.00 10.621 A 4 b PCB 4.5 0.1 15.0 750.0 750.15 11.44 -0.06 0.00 -46.50 0.06 2.162.641 A 4 c PCB 0.1 0.0 5.0 750.0 750.02 0.01 0.00 0.00 -0.93 0.00 0.871 A 5 b PCB 0.0 0.0 1.0 200.0 200.00 0.00 0.00 0.00 0.00 0.00 0.002 C 1 PCB 19.3 30.4 0.5 125.0 125.00 14.022.29 0.36 0.64 45.49 0.46 2.069.922 C 5 PCB 19.2 0.0 10.0 125.0 125.40 0.00 -0.27 0.00 -34.32 0.00 1.177.582 C 7 PCB 0.0 0.0 5.0 125.0 125.10 0.00 0.00 0.00 0.00 0.00 0.005 C PCB 0.0 0.0 7.0 200.0 200.12 0.01 0.00 0.00 0.05 0.00 0.00Total 47.2 32.1 14.063.76 5.427.89



(E2 + F2)(G ∙ D)2∑(D2)

D∑C J ∙ E ∙ 2

Austria’s Inform



86 U

mw

eltbundesamt

REP

-0723, Vienna 2020

Table 39: Uncertainty estimation of TSP emissions 1990 and 2018.


Year t emissions


(1)

Emission factor

uncertainty (1)



category in year x

Type A sensitivity

Type B sensitivity






uncertainty (3)



kt kt % % % % % % % % %

TSP Input data Input datainput data

Note Ainput data

Note A

*

Note BI·F


1 A 1 a TSP 0.8 1.1 8.0 40.0 40.79 1.35 0.01 0.02 0.37 0.23 0.191 A 1 b TSP 0.2 0.0 1.0 20.0 20.02 0.00 0.00 0.00 -0.02 0.00 0.001 A 1 c TSP 0.1 0.1 2.0 40.0 40.05 0.01 0.00 0.00 0.03 0.00 0.001 A 2 a TSP 0.1 0.0 5.0 125.0 125.10 0.00 0.00 0.00 -0.07 0.00 0.001 A 2 b TSP 0.0 0.0 5.0 125.0 125.10 0.00 0.00 0.00 0.00 0.00 0.001 A 2 c TSP 0.2 0.2 5.0 125.0 125.10 0.56 0.00 0.00 0.15 0.03 0.021 A 2 d TSP 1.1 0.2 10.0 125.0 125.40 0.59 -0.01 0.00 -1.23 0.06 1.521 A 2 e TSP 0.1 0.0 5.0 125.0 125.10 0.01 0.00 0.00 -0.12 0.00 0.021 A 2 f TSP 0.1 0.1 5.0 125.0 125.10 0.09 0.00 0.00 0.08 0.01 0.011 A 2 g 7 TSP 0.5 0.1 1.0 40.0 40.01 0.02 0.00 0.00 -0.18 0.00 0.031 A 2 g 8 TSP 0.3 0.3 10.0 40.0 41.23 0.08 0.00 0.00 0.04 0.07 0.011 A 3 a TSP 0.0 0.1 3.0 40.0 40.11 0.02 0.00 0.00 0.07 0.01 0.011 A 3 b 1 TSP 1.6 0.9 3.1 40.0 40.12 0.81 -0.01 0.02 -0.23 0.07 0.061 A 3 b 2 TSP 0.8 0.2 3.1 40.0 40.12 0.04 -0.01 0.00 -0.31 0.02 0.091 A 3 b 3 TSP 2.5 0.3 3.1 40.0 40.12 0.08 -0.03 0.01 -1.13 0.02 1.281 A 3 b 4 TSP 0.1 0.1 3.1 40.0 40.12 0.01 0.00 0.00 0.00 0.01 0.001 A 3 b 6 TSP 1.1 1.9 3.1 125.0 125.04 39.87 0.02 0.04 2.77 0.16 7.691 A 3 b 7 TSP 0.9 1.6 3.1 125.0 125.04 27.83 0.02 0.03 2.30 0.13 5.291 A 3 c TSP 2.0 1.6 3.0 40.0 40.11 2.83 0.00 0.03 0.13 0.13 0.031 A 3 d TSP 0.1 0.0 3.0 40.0 40.11 0.00 0.00 0.00 -0.05 0.00 0.001 A 3 e TSP 0.0 0.0 2.0 125.0 125.02 0.00 0.00 0.00 0.01 0.00 0.001 A 4 a TSP 0.9 0.3 5.0 125.0 125.10 1.13 -0.01 0.01 -0.80 0.04 0.641 A 4 b TSP 11.6 6.8 15.0 125.0 125.90 494.21 -0.03 0.13 -3.76 2.70 21.451 A 4 c TSP 2.6 1.0 5.0 125.0 125.10 9.99 -0.02 0.02 -2.14 0.13 4.581 A 5 b TSP 0.0 0.0 1.0 125.0 125.00 0.00 0.00 0.00 0.01 0.00 0.001 B 1 a TSP 0.9 0.4 5.0 200.0 200.06 3.81 0.00 0.01 -0.91 0.05 0.822 A 1 TSP 0.2 0.1 1.1 200.0 200.00 0.10 0.00 0.00 -0.25 0.00 0.062 A 2 TSP 0.1 0.1 1.6 200.0 200.01 0.22 0.00 0.00 0.17 0.00 0.032 A 5 TSP 10.0 12.8 5.0 200.0 200.06 4.499.68 0.11 0.24 21.26 1.71 454.702 B-10 TSP 1.0 0.3 2.0 20.0 20.10 0.03 -0.01 0.01 -0.13 0.02 0.022 C 1 TSP 6.4 0.7 0.5 40.0 40.00 0.51 -0.07 0.01 -2.96 0.01 8.792 C 2 TSP 0.0 0.0 5.0 40.0 40.31 0.00 0.00 0.00 0.00 0.00 0.002 C 3 TSP 0.1 0.0 2.0 40.0 40.05 0.00 0.00 0.00 -0.06 0.00 0.002 C 5 TSP 0.0 0.0 10.0 40.0 41.23 0.00 0.00 0.00 0.00 0.00 0.002 C 7 TSP 0.0 0.0 5.0 40.0 40.31 0.00 0.00 0.00 -0.01 0.00 0.002 G TSP 0.6 0.5 100.0 125.0 160.08 3.84 0.00 0.01 0.04 1.25 1.562 H TSP 0.0 0.0 10.0 200.0 200.25 0.00 0.00 0.00 0.00 0.00 0.002 I TSP 0.9 1.1 1.0 40.0 40.01 1.39 0.01 0.02 0.35 0.03 0.133 B 1 TSP 0.6 0.4 1.0 200.0 200.00 5.50 0.00 0.01 0.05 0.01 0.003 B 2 TSP 0.1 0.1 10.0 200.0 200.25 0.25 0.00 0.00 0.16 0.03 0.033 B 3 TSP 0.3 0.3 4.0 200.0 200.04 1.86 0.00 0.00 0.06 0.03 0.003 B 4 TSP 0.2 0.3 10.0 200.0 200.25 2.60 0.00 0.01 0.54 0.08 0.293 D c TSP 3.6 3.3 5.0 200.0 200.06 304.01 0.01 0.06 2.91 0.44 8.693 D d TSP 0.0 0.1 5.0 200.0 200.06 0.09 0.00 0.00 0.13 0.01 0.023 F TSP 0.1 0.0 100.0 125.0 160.08 0.01 0.00 0.00 -0.10 0.08 0.025 A TSP 0.1 0.5 12.0 200.0 200.36 6.62 0.01 0.01 1.46 0.16 2.165 C TSP 0.0 0.0 7.0 200.0 200.12 0.00 0.00 0.00 0.00 0.00 0.005 E TSP 0.2 0.2 50.0 200.0 206.16 1.18 0.00 0.00 0.20 0.27 0.11Total 53.2 38.3 5.411.26 520.35



(E2 + F2)(G ∙ D)2∑(D2)

D∑C J ∙ E ∙ 2

Austria’s Inform



Um

weltbundesam

t R

EP-0723, V

ienna 2020 87

Table 40: Uncertainty estimation of PM10 emissions 1990 and 2018.


Year t emissions


(1)

Emission factor

uncertainty (1)



category in year x

Type A sensitivity

Type B sensitivity






uncertainty (3)



kt kt % % % % % % % % %

PM10 Input data Input datainput data

Note Ainput data

Note A

*

Note BI·F


1 A 1 a PM10 0.8 1.0 8.0 125.0 125.26 21.85 0.01 0.02 1.47 0.27 2.221 A 1 b PM10 0.1 0.0 1.0 40.0 40.01 0.00 0.00 0.00 -0.04 0.00 0.001 A 1 c PM10 0.1 0.1 2.0 40.0 40.05 0.02 0.00 0.00 0.04 0.01 0.001 A 2 a PM10 0.1 0.0 5.0 125.0 125.10 0.00 0.00 0.00 -0.07 0.00 0.001 A 2 b PM10 0.0 0.0 5.0 125.0 125.10 0.00 0.00 0.00 0.00 0.00 0.001 A 2 c PM10 0.2 0.2 5.0 125.0 125.10 0.96 0.00 0.01 0.22 0.04 0.051 A 2 d PM10 0.9 0.2 10.0 125.0 125.40 1.01 -0.01 0.01 -1.23 0.07 1.511 A 2 e PM10 0.1 0.0 5.0 125.0 125.10 0.02 0.00 0.00 -0.12 0.01 0.011 A 2 f PM10 0.1 0.1 5.0 125.0 125.10 0.15 0.00 0.00 0.11 0.01 0.011 A 2 g 7 PM10 0.5 0.1 1.0 40.0 40.01 0.04 0.00 0.00 -0.20 0.00 0.041 A 2 g 8 PM10 0.3 0.2 10.0 40.0 41.23 0.13 0.00 0.01 0.06 0.08 0.011 A 3 a PM10 0.0 0.1 3.0 40.0 40.11 0.03 0.00 0.00 0.10 0.01 0.011 A 3 b 1 PM10 1.6 0.9 3.1 40.0 40.12 1.70 0.00 0.02 -0.18 0.09 0.041 A 3 b 2 PM10 0.8 0.2 3.1 40.0 40.12 0.09 -0.01 0.00 -0.34 0.02 0.111 A 3 b 3 PM10 2.5 0.3 3.1 40.0 40.12 0.17 -0.03 0.01 -1.29 0.03 1.671 A 3 b 4 PM10 0.1 0.1 3.1 125.0 125.04 0.21 0.00 0.00 0.05 0.01 0.001 A 3 b 6 PM10 0.8 1.5 3.1 125.0 125.04 47.56 0.02 0.04 2.88 0.16 8.331 A 3 b 7 PM10 0.4 0.8 3.1 125.0 125.04 14.66 0.01 0.02 1.60 0.09 2.551 A 3 c PM10 1.0 0.6 3.0 40.0 40.11 0.75 0.00 0.01 -0.05 0.06 0.011 A 3 d PM10 0.1 0.0 3.0 40.0 40.11 0.00 0.00 0.00 -0.05 0.00 0.001 A 3 e PM10 0.0 0.0 2.0 125.0 125.02 0.00 0.00 0.00 0.01 0.00 0.001 A 4 a PM10 0.9 0.3 5.0 125.0 125.10 2.16 -0.01 0.01 -0.74 0.05 0.551 A 4 b PM10 10.8 6.3 15.0 125.0 125.90 910.58 -0.02 0.15 -1.95 3.28 14.571 A 4 c PM10 2.6 0.9 5.0 125.0 125.10 19.10 -0.02 0.02 -2.24 0.16 5.021 A 5 b PM10 0.0 0.0 1.0 125.0 125.00 0.01 0.00 0.00 0.02 0.00 0.001 B 1 a PM10 0.4 0.2 5.0 200.0 200.06 1.80 0.00 0.00 -0.41 0.03 0.172 A 1 PM10 0.2 0.1 1.1 200.0 200.00 0.17 0.00 0.00 -0.23 0.00 0.052 A 2 PM10 0.1 0.1 1.6 200.0 200.01 0.38 0.00 0.00 0.22 0.00 0.052 A 5 PM10 4.7 6.1 5.0 200.0 200.06 2.140.88 0.07 0.15 14.92 1.06 223.622 B-10 PM10 0.6 0.2 2.0 20.0 20.10 0.02 0.00 0.00 -0.08 0.01 0.012 C 1 PM10 4.6 0.5 0.5 40.0 40.00 0.54 -0.06 0.01 -2.40 0.01 5.762 C 2 PM10 0.0 0.0 5.0 40.0 40.31 0.00 0.00 0.00 0.00 0.00 0.002 C 3 PM10 0.1 0.0 2.0 40.0 40.05 0.00 0.00 0.00 -0.05 0.00 0.002 C 5 PM10 0.0 0.0 10.0 40.0 41.23 0.00 0.00 0.00 0.00 0.00 0.002 C 7 PM10 0.0 0.0 5.0 40.0 40.31 0.00 0.00 0.00 -0.01 0.00 0.002 G PM10 0.6 0.5 100.0 125.0 160.08 7.73 0.00 0.01 0.20 1.59 2.552 H PM10 0.0 0.0 10.0 200.0 200.25 0.00 0.00 0.00 0.00 0.00 0.002 I PM10 0.4 0.5 1.0 40.0 40.01 0.47 0.01 0.01 0.21 0.02 0.043 B 1 PM10 0.3 0.2 1.0 200.0 200.00 2.35 0.00 0.00 0.13 0.01 0.023 B 2 PM10 0.0 0.0 10.0 200.0 200.25 0.11 0.00 0.00 0.11 0.01 0.013 B 3 PM10 0.2 0.1 4.0 200.0 200.04 0.79 0.00 0.00 0.09 0.02 0.013 B 4 PM10 0.1 0.1 10.0 200.0 200.25 1.11 0.00 0.00 0.35 0.05 0.133 D c PM10 3.6 3.3 5.0 200.0 200.06 640.45 0.03 0.08 5.09 0.58 26.233 D d PM10 0.0 0.0 5.0 200.0 200.06 0.04 0.00 0.00 0.08 0.00 0.013 F PM10 0.1 0.0 100.0 125.0 160.08 0.03 0.00 0.00 -0.11 0.10 0.025 A PM10 0.1 0.2 12.0 200.0 200.36 3.12 0.00 0.01 0.92 0.10 0.865 C PM10 0.0 0.0 7.0 200.0 200.12 0.00 0.00 0.00 0.00 0.00 0.005 E PM10 0.2 0.2 50.0 200.0 206.16 2.49 0.00 0.00 0.34 0.35 0.24Total 40.9 26.4 3.823.69 296.52



(E2 + F2)(G ∙ D)2∑(D2)

D∑C J ∙ E ∙ 2

Austria’s Inform



88 U

mw

eltbundesamt

REP

-0723, Vienna 2020

Table 41: Uncertainty estimation of PM2.5 emissions 1990 and 2018.


Year t emissions


(1)

Emission factor

uncertainty (1)



category in year x

Type A sensitivity

Type B sensitivity






uncertainty (3)



kt kt % % % % % % % % %

PM2.5 Input data Input datainput data

Note Ainput data

Note A

*

Note BI·F


1 A 1 a PM2.5 0.7 0.8 8.0 60.0 60.53 12.18 0.02 0.03 1.05 0.34 1.221 A 1 b PM2.5 0.1 0.0 1.0 40.0 40.01 0.01 0.00 0.00 -0.04 0.00 0.001 A 1 c PM2.5 0.1 0.1 2.0 40.0 40.05 0.06 0.00 0.00 0.08 0.01 0.011 A 2 a PM2.5 0.0 0.0 5.0 125.0 125.10 0.01 0.00 0.00 -0.06 0.00 0.001 A 2 b PM2.5 0.0 0.0 5.0 125.0 125.10 0.00 0.00 0.00 0.01 0.00 0.001 A 2 c PM2.5 0.2 0.2 5.0 125.0 125.10 2.29 0.00 0.01 0.37 0.04 0.141 A 2 d PM2.5 0.8 0.2 10.0 125.0 125.40 2.34 -0.01 0.01 -1.08 0.09 1.181 A 2 e PM2.5 0.1 0.0 5.0 125.0 125.10 0.05 0.00 0.00 -0.10 0.01 0.011 A 2 f PM2.5 0.1 0.1 5.0 125.0 125.10 0.36 0.00 0.00 0.18 0.02 0.031 A 2 g 7 PM2.5 0.5 0.1 1.0 40.0 40.01 0.14 -0.01 0.00 -0.21 0.01 0.041 A 2 g 8 PM2.5 0.2 0.2 10.0 60.0 60.83 0.67 0.00 0.01 0.17 0.10 0.041 A 3 a PM2.5 0.0 0.1 3.0 40.0 40.11 0.12 0.00 0.00 0.15 0.02 0.021 A 3 b 1 PM2.5 1.6 0.9 3.1 125.0 125.04 56.74 0.00 0.03 0.06 0.14 0.021 A 3 b 2 PM2.5 0.8 0.2 3.1 125.0 125.04 3.08 -0.01 0.01 -1.11 0.03 1.241 A 3 b 3 PM2.5 2.5 0.3 3.1 125.0 125.04 5.52 -0.04 0.01 -4.71 0.04 22.201 A 3 b 4 PM2.5 0.1 0.1 3.1 125.0 125.04 0.71 0.00 0.00 0.14 0.02 0.021 A 3 b 6 PM2.5 0.4 0.8 3.1 125.0 125.04 47.94 0.02 0.03 2.60 0.13 6.771 A 3 b 7 PM2.5 0.2 0.4 3.1 125.0 125.04 14.66 0.01 0.02 1.43 0.07 2.051 A 3 c PM2.5 0.6 0.2 3.0 40.0 40.11 0.34 0.00 0.01 -0.16 0.03 0.031 A 3 d PM2.5 0.1 0.0 3.0 40.0 40.11 0.01 0.00 0.00 -0.06 0.00 0.001 A 3 e PM2.5 0.0 0.0 2.0 125.0 125.02 0.00 0.00 0.00 0.01 0.00 0.001 A 4 a PM2.5 0.8 0.3 5.0 60.0 60.21 1.54 0.00 0.01 -0.25 0.08 0.071 A 4 b PM2.5 10.1 6.0 15.0 60.0 61.85 676.24 0.03 0.22 1.52 4.68 24.231 A 4 c PM2.5 2.5 0.9 5.0 100.0 100.12 37.89 -0.02 0.03 -1.65 0.23 2.771 A 5 b PM2.5 0.0 0.0 1.0 125.0 125.00 0.02 0.00 0.00 0.04 0.00 0.001 B 1 a PM2.5 0.1 0.1 5.0 200.0 200.06 0.61 0.00 0.00 -0.01 0.01 0.002 A 1 PM2.5 0.1 0.0 1.1 40.0 40.02 0.02 0.00 0.00 -0.04 0.00 0.002 A 2 PM2.5 0.0 0.1 1.6 125.0 125.01 0.26 0.00 0.00 0.17 0.00 0.032 A 5 PM2.5 0.5 0.7 5.0 200.0 200.06 92.22 0.01 0.03 2.99 0.18 8.952 B-10 PM2.5 0.3 0.1 2.0 20.0 20.10 0.02 0.00 0.00 -0.04 0.01 0.002 C 1 PM2.5 2.1 0.2 0.5 20.0 20.01 0.09 -0.03 0.01 -0.64 0.01 0.402 C 2 PM2.5 0.0 0.0 5.0 40.0 40.31 0.00 0.00 0.00 0.01 0.00 0.002 C 3 PM2.5 0.0 0.0 2.0 40.0 40.05 0.00 0.00 0.00 -0.02 0.00 0.002 C 5 PM2.5 0.0 0.0 10.0 40.0 41.23 0.00 0.00 0.00 0.00 0.00 0.002 C 7 PM2.5 0.0 0.0 5.0 40.0 40.31 0.00 0.00 0.00 -0.01 0.00 0.002 G PM2.5 0.5 0.4 100.0 125.0 160.08 20.96 0.00 0.02 0.58 2.12 4.842 H PM2.5 0.0 0.0 10.0 200.0 200.25 0.00 0.00 0.00 0.00 0.00 0.002 I PM2.5 0.1 0.2 1.0 40.0 40.01 0.26 0.00 0.01 0.15 0.01 0.023 B 1 PM2.5 0.1 0.0 1.0 200.0 200.00 0.40 0.00 0.00 0.10 0.00 0.013 B 2 PM2.5 0.0 0.0 10.0 200.0 200.25 0.02 0.00 0.00 0.04 0.00 0.003 B 3 PM2.5 0.0 0.0 4.0 200.0 200.04 0.13 0.00 0.00 0.06 0.01 0.003 B 4 PM2.5 0.0 0.0 10.0 200.0 200.25 0.19 0.00 0.00 0.14 0.02 0.023 D c PM2.5 0.1 0.1 5.0 200.0 200.06 3.25 0.00 0.00 0.42 0.03 0.173 D d PM2.5 0.0 0.0 5.0 200.0 200.06 0.01 0.00 0.00 0.04 0.00 0.003 F PM2.5 0.1 0.0 100.0 125.0 160.08 0.09 0.00 0.00 -0.11 0.14 0.035 A PM2.5 0.0 0.1 12.0 200.0 200.36 1.06 0.00 0.00 0.46 0.05 0.215 C PM2.5 0.0 0.0 7.0 200.0 200.12 0.00 0.00 0.00 0.00 0.00 0.005 E PM2.5 0.2 0.2 50.0 200.0 206.16 8.52 0.00 0.01 0.69 0.53 0.75Total 27.2 14.3 991.06 77.56



(E2 + F2)D∑C

J ∙ E ∙ 2(G ∙ D)2∑(D2)



1.8 Completeness

The emission data presented in this report were compiled according to the revised 2014 Report-ing Guidelines (ECE/EB.AIR.125) approved by the Executive Body for the UNECE/LRTAP Con-vention at its 36th session.

The inventory is complete with regard to reported gases, reported years and reported emissions from all sources, and also complete in terms of geographic coverage.

Geographic Coverage

The geographic coverage is complete. There is no territory in Austria not covered by the inventory.

However, if fuel prices vary considerably in neighbouring countries, fuel sold within the territory of a Party is used outside its territory (so-called ‘fuel export’). Austria has experienced a consid-erable amount of ‘fuel export’ in the last few years (see also Chapter 2.5).

According to the revised 2014 Reporting Guidelines (ECE/EB.AIR.125), Parties within the EMEP region should calculate and report emissions, consistent with national energy balances reported to Eurostat or the International Energy Agency (IEA). Emissions from road vehicle transport should therefore be calculated and reported on the basis of the fuel sold. In addition, Parties may voluntarily report emissions from road vehicles based on fuel used in the geographic area of the Party.

Emissions of the Austrian road transport sector are therefore generally reported on the basis of fuel sold. With respect to compliance with the 2010 emission ceilings under Directive (EU) 2016/2284 on the reduction of national emissions of certain atmospheric pollutants, emissions are accounted on the basis of ‘fuel used’. The Austrian NEC Totals therefore differ from the LRTAP Totals presented in this report (see Appendix, Chapter 12.2).

Gases, Reporting Years

In accordance with the Austrian obligation, all relevant pollutants mentioned in Table 3 (minimum reporting programme), are covered by the Austrian inventory and are reported for the years 1990–2018 for the main pollutants, from 1990 onwards for POPs and HMs and for the years 1990, 1995 and from 2000 onwards for PM.

In submission 2020 Austria reports for the first time all pollutants in the NFR19 reporting format from 1990 to the latest inventory year. Emissions of the years before 1990 were last updated and published in submission 201465.

Notation Keys

Notation keys are used according to the revised 2014 Reporting Guidelines (ECE/EB.AIR.125) (see Table 42) to indicate where emissions are not occurring in Austria, where emissions have not been estimated or have been included elsewhere as suggested by EMEP/EEA Emission In-ventory Guidebook 2016.

65 Austria´s submission 2014 under the Convention on Long-range Transboundary Air Pollution covering the years

1980–2012: http://www.ceip.at/ms/ceip_home1/ceip_home/status_reporting/2014_submissions/




Table 42: Notation keys used in the NFR.

Abbreviation Meaning Objective

NA not applicable is used for activities in a given source category which are believed not to result in significant emissions of a specific compound;

NE not estimated for activity data and/or emissions by sources of pollutants which have not been estimated but for which a corresponding activity may occur within a Party. Where NE is used in an inventory to report emissions of pollutants, the Party should indicate in the IIR why such emissions have not been estimated. Furthermore, a Party may consider that a disproportionate amount of effort would be required to collect data for a pollutant from a specific category that would be insignificant in terms of the overall level and trend in national emissions and in such cases use the notation key NE. The Party should in the IIR provide justifications for their use of NE notation keys, e.g., lack of robust data, lack of methodology etc. Once emissions from a specific category have been reported in a previous submission, emissions from this specific category should be reported in subsequent inventory submissions;

IE included elsewhere

for emissions by sources of pollutants estimated but included elsewhere in the inventory instead of under the expected source category. Where IE is used in an inventory, the Party should indicate, in the IIR, where in the inventory the emissions for the displaced source category have been included, and the Party should explain such a deviation from the inclusion under the expected category, especially if it is due to confidentiality;

C confidential (confidential information), for emissions by sources of pollutants of which the reporting could lead to the disclosure of confidential information. The source category where these emissions are included should be indicated;

NO not occurring for categories or processes within a particular source category that do not occur within a Party;

NR not relevant according to paragraph 37 in the Guidelines, emission inventory reporting for the main pollutants should cover all years from 1990 onwards if data are available. However, NR is introduced to ease the reporting where reporting of emissions is not strictly required by the different protocols, e.g., emissions for some Parties prior to agreed base years.

Assessment of transparency and completeness

In the Austrian QMS a transparency and completeness index is used to quantify the quality of the inventory, calculated as follows: Transparency [%] = [1 – (number of IE/number of estimates)]*100 Completeness [%] = [1 – (number of NE/number of estimates)]*100

The total number of data records (emission data) are counted as well as the numbers reported as ‘not estimated’ and ‘included elsewhere’. Then the share of ‘NE’ and ‘IE’ to total data records are determined. The result of this years’ analysis is shown in Table 43. As can be seen the completeness pa-rameter is very high. For PAHs the lowest completeness was investigated, which is due to not estimated PAH emissions from sectorsTransport (international and domestic aviation), Industrial Processes and Product Use (Chemical Industry: other66, Ferroalloys Production, Aluminium Production, Copper Production, Other Metal Production) and Waste (Other Waste).

66 PAH emissions from graphite production (production of graphite electrodes only) are not estimated, as no emission

factor is available.



The transparency analysis for the reporting year 2018 shows also a high transparency of the Austrian inventory. For SO2 the largest number of ‘IE’ has been identified, which was applied for eleven sub-categories. Explanations are provided in the respective sector chapters on ‘Com-pleteness’.

Table 43: Transparency and completeness in submission 2020.

Pollutants Submission 2020 IE NE Transparency Completeness NOx (as NO2) 10 1 99% 92% NMVOC 10 3 98% 92% SOx (as SO2) 11 1 99% 91% NH3 9 0 100% 93% PM2.5 6 5 96% 95% PM10 6 5 96% 95% TSP 6 5 96% 95% CO 8 2 98% 94% Pb 7 2 98% 94% Cd 7 2 98% 94% Hg 7 3 98% 94% PCDD/PCDF 7 4 97% 94% PAHs (total) 7 8 94% 94% HCB 7 6 95% 94% PCBs 7 3 98% 94%

Austria’s Informative Inventory Report (IIR) 2020 – Explanations of Key Trends


2 EXPLANATIONS OF KEY TRENDS

This chapter describes the trends and the drivers of air pollutant emissions which Austria is obliged to report based on the following listed protocols. Additionally the trends of SO2, NOx, NH3, NMVOC and PM2.5 emissions not including fuel exports (fuel used) as reported under Di-rective (EU) 2016/2284 on the reduction of national emissions of certain atmospheric pollutants are described in chapter 2.5. From submission 2019 onwards Austria reports all mandatory pollutants in the NFR19 reporting format from 1990 to the latest inventory year. Emissions of the years before 1990 were last up-dated and published in submission 201467.

1985 Helsinki Protocol on the Reduction of Sulphur Emissions or their Transboundary Fluxes: This protocol requires parties to reduce their sulphur emissions by at least 30%. All par-ties achieved this reduction target by the target year 1993. In 2017, Austria’s SO2 emissions were 83% lower than in 1990. 1988 Sofia Protocol concerning the Control of Emissions of Nitrogen Oxides or their Transboundary Fluxes: This Protocol requires as a first step, to freeze emissions of nitrogen oxides or their transboundary fluxes. The general reference year is 1987. The second step to the NOx Protocol requires the application of an effects-based approach to further reduce emissions of nitrogen compounds. Nineteen of the 25 Parties to the 1988 NOx Protocol have reached the target and stabilized emissions at 198768 levels or reduced emissions below that level according to the latest emission data reported. Austria was successful in fulfilling the stabilisation target set out in the Protocol. Since 2003–2005, when emissions reached an all-time high due to a considerable increase of fuel export and the failure of European provisions for the reduction of vehicle emissions, NOx emissions are decreasing.

1991 Geneva Protocol concerning the Control of Emissions of Volatile Organic Com-pounds or their Transboundary Fluxes: This Protocol specifies three options for emission re-duction targets that have to be chosen upon signature or upon ratification. Austria chose the op-tion which requires a 30% reduction of VOCs by 1999 using a base year between 1984 and 1990 and chose 1988 as base year. Austria met the reduction target.

1998 Aarhus Protocol on Heavy Metals: It targets three particularly harmful metals: cadmium, lead and mercury. According to one of the basic obligations, Parties have to reduce their emis-sions for these three metals below their levels in the reference year. Austria has chosen 1985 as the reference year and current emissions are well below the level of the reference year.

1998 Aarhus Protocol on Persistent Organic Pollutants (POPs): The protocol focuses on a list of 16 substances that were singled out according to agreed risk criteria. These substances comprise eleven pesticides, two industrial chemicals and three by-products/contaminants. The ultimate objective is to eliminate any discharges, emissions and losses of POPs. Parties have to reduce their emissions for PAHs, Dioxins/Furans and HCB below their levels in the reference year. Austria has chosen 1985 as the reference year and current emissions are well below the level of the reference year. 1999 Gothenburg Protocol to Abate Acidification, Eutrophication and Ground-level Ozone “Multi-Effect Protocol”: The Protocol sets emission ceilings for 2010 for four pollu-tants: sulphur, NOx, VOCs and ammonia. In May 2012 the protocol was amended to include na-tional emission reduction commitments to be achieved in 2020 and beyond. Austria has not rati-fied the Protocol and is not Party to the Protocol, but reports the concerned emissions. 67 Austria´s submission 2014 under the Convention on Long-range Transboundary Air Pollution covering the years

1980–2012: http://www.ceip.at/ms/ceip_home1/ceip_home/status_reporting/2014_submissions/ 68 or in the case of the United States 1978




2.1 Emission Trends for Air Pollutants covered by the Multi-Effect Protocol as well as CO

National total emissions and trends (1990–2018) for air pollutants covered by the Multi-Effect Protocol are shown in Table 44. Please note that emissions from mobile sources are calculated based on fuel sold in Austria, thus national total emissions include ‘fuel export’. Austria’s emis-sions based on fuel used – thus excluding ‘fuel export’ – are presented in Chapter 2.5.

Table 44: National total emissions and trends 1990–2018 for air pollutants covered by the Multi-Effect Protocol and CO.

Year Emission [kt] SO2 NOx NMVOC NH3 CO

1990 73.70 217.22 334.02 61.73 1 249.41

1991 70.72 226.75 328.31 62.57 1 256.55

1992 54.19 215.32 304.70 61.08 1 199.64

1993 52.82 206.77 284.67 62.07 1 137.53

1994 47.19 198.56 262.22 62.02 1 071.60

1995 46.81 197.88 246.57 63.11 967.74

1996 43.93 215.68 237.20 62.46 962.42

1997 40.40 201.89 223.01 62.73 888.02

1998 35.63 213.68 214.58 63.11 842.63

1999 33.74 205.43 203.49 61.91 726.15

2000 31.58 211.10 179.79 60.58 721.69

2001 32.46 221.81 174.09 60.66 695.04

2002 31.39 229.69 168.94 59.99 664.09

2003 31.17 240.90 165.74 60.07 666.46

2004 26.60 240.59 152.83 59.94 649.61

2005 25.95 246.14 157.11 59.87 624.59

2006 26.79 236.09 159.25 60.32 624.41

2007 23.44 228.56 154.80 61.64 601.23

2008 20.33 215.12 148.94 61.31 581.96

2009 14.80 201.09 135.51 62.73 561.34

2010 16.04 202.15 135.41 62.69 577.39

2011 15.23 194.02 129.93 62.13 560.10

2012 14.86 188.87 127.42 62.41 559.71

2013 14.44 188.07 121.56 62.48 564.19

2014 14.54 179.43 114.63 63.23 528.63

2015 13.98 176.36 111.44 64.01 541.56

2016 13.32 170.30 109.73 64.81 537.84

2017 12.84 161.95 110.73 65.67 529.08

2018 11.77 150.86 107.22 64.63 490.09

Trend 1990–2018 -84.0% -30.5% -67.9% 4.7% -60.8%



2.1.1 SO2 Emissions

In 1990, national total SO2 emissions amounted to 74 kt. Since then emissions have decreased quite steadily. In the year 2018, emissions were reduced by 84.0% compared to 1990 and amounted to 12 kt. This decline is mainly caused by a reduction of the sulphur content in miner-al oil products and fuels (according to the Austrian Fuel Ordinance), the installation of desul-phurisation units in plants (according to the Clean Air Act for boilers) and an increased use of low-sulphur fuels like natural gas. The economic crisis in 2009 caused a decrease in emis-sions, followed by an increase due to the recovery of the economy. The strong reduction in emissions between 1991 and 1992 can be explained by reduced coal consumption in power plants (1.A.1.a) and a reduction of SO2 emissions from oil fired power plants (1.A.1.a) as well as from iron and steel (1.A.2.a) and pulp and paper (1.A.2.d) production. From 2017 to 2018 emis-sions decreased by 8.4%. This was mainly caused by reductions in emissions from iron and steel (1.A.2.a).

Main sources and emission trends in Austria As shown in Figure 7 the main source of SO2 emissions in Austria in 2018 is NFR sector 1.A Fuel Combustion Activities with 95% in national total SO2 emissions. Sector 2 Industrial Pro-cesses and Product Use contributes with 4.8%.

NFR sectors 1.B Fugitive Emissions, 3 Agriculture and 5 Waste are only minor contributors to national total SO2 emissions in 2018 with 0.2%, 0.01% and 0.1%, respectively.

Figure 7: Share of NFR sectors 2018 in SO2 emissions.

1.A Fuel Combustion Activities

As shown in Table 45 the main source for SO2 emissions in Austria, with a share of 95% in both years, 1990 and 2018, is category 1.A Fuel Combustion Activities. Within this source, the main contributors to total SO2 emissions are 1.A.2 Manufacturing Industries with 66% (more than half of the emissions stem from iron and steel industry), 1.A.4 Other Sectors (residential heating) with 12% and 1.A.1 Energy Industries with 14%.

94,8%

0,2% 4,8% 0,01% 0,1%

Share of NFR sectors 2018 – SO2 emissions

1.A FUEL COMBUSTION ACTIVITIES

1.B FUGITIVE EMISSIONS FROM FUELS

2 INDUSTRIAL PROCESSES AND PRODUCTUSE

3 AGRICULTURE

5 WASTE




The constant decrease of emissions since 1990 from 1.A.1 Energy Industries, 1.A.2 Manufac-turing Industries and Construction, 1.A.3 Transport and 1.A.4 Other Sectors (mainly residential heating) is mainly due to: a lowering of the sulphur content in mineral oil products and fuels (due to e.g. Fuel Ordi-

nance69), a switch-over from high sulfur fuels to low-sulphur fuels or to even sulphur free fuel (e.g. natu-

ral gas) – sulphur-free fuels, such as those offered nationwide in Austria since 2006, are a precondition for the use of advanced exhaust gas after treatment technologies.

implementation of desulphurisation units in power plants (due to e.g. LCP directive70 and pre-ceding national legislation),

abatement techniques like combined flue gas treatment. 2 Industrial Processes and Product Use The share in national total SO2 emissions from NFR sector 2 Industrial Processes and Product Use in 2018 is 4.8%. Within this source, SO2 emissions result from 2.B Chemical Industry (64%) and 2.C Metal Production (35%). In both subcategories emissions have decreased since 1990 mainly caused by abatement techniques such as systems for purification of waste gases and desulfurization facilities, as well as due to improved processes.

Figure 8: SO2 emissions in Austria 1990–2018 by sectors in absolute terms.

69 BGBl_II_417-04_Kraftstoffverordnung; idF. BGBl. II Nr. 398/2012 70 Luftreinhaltegesetzes für Kesselanlagen (LRG-K) BGBl. I Nr. 127/2013 (older version: BGBl. Nr. 380/1988 idF.

BGBl. Nr. 185/1993, BGBl. I Nr. 150/2004; Umsetzung der Richtlinie 96/61/EG; Richtlinie 96/82/EG, Richtlinie 88/609/EWG, Richtlinie 2001/80/EG, Richtlinie 2002/49/EG)

0

10

20

30

40

50

60

70

80

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

2014

2016

2018

SO2 e

mis

sion

s [k

t]

SO2 emissions in Austria 1990 - 2018 by NFR sectors

5 WASTE

3 AGRICULTURE

2 INDUSTRIAL PROCESSES AND PRODUCTUSE1.B FUGITIVE EMISSIONS FROM FUELS

1.A.5 Other

1.A.4 Other Sectors

1.A.3 Transport

1.A.2 Manufacturing Industries & Construction

1.A.1 Energy Industries




Table 45: SO2 emissions per NFR Category 1990 and 2018, trend 1990–2018 and share in total emissions.

NFR Category SO2 Emission in [kt] Trend Share in National Total

1990 2018 1990–2018

2017–2018

1990 2018

1 ENERGY 71.69 11.18 -84% -9% 97% 95%

1.A FUEL COMBUSTION ACTIVITIES 69.69 11.16 -84% -9% 95% 95%

1.A.1 Energy Industries 14.07 1.62 -88% 22% 19% 14%

1.A.1.a Public Electricity and Heat Production 11.81 0.96 -92% -2% 16% 8%

1.A.1.b Petroleum refining 2.25 0.66 -71% 86% 3% 6%

1.A.1.c Manufacture of Solid fuels & Other Energy Ind. 0.00 0.00 -58% -8% <1% <1%

1.A.2 Manufacturing Industries and Construction 17.83 7.81 -56% -13% 24% 66%

1.A.2.a Iron and Steel 6.73 4.26 -37% -13% 9% 36%

1.A.2.b Non-ferrous Metals 0.18 0.09 -50% -16% <1% 1%

1.A.2.c Chemicals 0.66 0.28 -58% -23% 1% 2%

1.A.2.d Pulp, Paper and Print 4.30 0.81 -81% -16% 6% 7%

1.A.2.e Food Processing, Beverages and Tobacco 1.65 0.12 -93% -22% 2% 1%

1.A.2.f Non-metallic Minerals 2.23 0.91 -59% 2% 3% 8%

1.A.2.g Manufacturing Industries and Constr. - other 2.08 1.36 -35% -17% 3% 12%

1.A.3 Transport 5.13 0.29 -94% -2% 7% 2%

1.A.3.a Civil Aviation 0.03 0.10 194% 9% <1% 1%

1.A.3.b Road Transportation 4.78 0.14 -97% <1% 6% 1%

1.A.3.c Railways 0.26 0.04 -85% -18% <1% <1%

1.A.3.d Navigation 0.05 0.01 -68% -26% <1% <1%

1.A.3.e Other transportation 0.00 0.00 162% -7% <1% <1%

1.A.4 Other Sectors 32.66 1.42 -96% -11% 44% 12%

1.A.4.a Commercial/Institutional 4.95 0.08 -98% -30% 7% 1%

1.A.4.b Residential 25.93 1.25 -95% -10% 35% 11%

1.A.4.c Agriculture/Forestry/Fisheries 1.78 0.09 -95% -16% 2% 1%

1.A.5 Other 0.01 0.02 28% 1% <1% <1%

1.B FUGITIVE EMISSIONS FROM FUELS 2.00 0.02 -99% -36% 3% <1%

2 INDUSTRIAL PROCESSES AND PRODUCT USE

1.93 0.57 -71% <1% 3% 5%

2.A MINERAL PRODUCTS IE IE IE IE IE IE

2.B CHEMICAL INDUSTRY 1.56 0.37 -77% <1% 2% 3%

2.C METAL PRODUCTION 0.36 0.20 -45% <1% <1% 2%

2.D NON ENERGY PRODUCTS/ SOLVENTS NA NA NA NA NA NA

2.G Other product manufacture and use 0.00 0.00 -32% -10% <1% <1%

2.H Other Processes NA NA NA NA NA NA

2.I Wood processing NA NA NA NA NA NA

2.J Production of POPs NO NO NO NO NO NO

2.K "Consumption of POPs and heavy metals NO NO NO NO NO NO

2.L Other production, consumption, storage, transportation or handling of bulk products

NO NO NO NO NO NO

3 AGRICULTURE 0.01 0.00 -73% -1% <1% <1%

5 WASTE 0.07 0.01 -81% 1% <1% <1%

Total without sinks 73.70 11.77 -84% -8%



2.1.2 NOx Emissions

In 1990, national total NOx emissions amounted to 217 kt. After an all-time high of emissions be-tween 2003 and 2005 emissions are decreasing continuously. This is mainly due to reduced emissions from heavy trucks, especially because of improvements in the after treatment tech-nology. In 2018, NOx emissions amounted to 151 kt and were about 31% lower than in 1990. From 2017 to 2018 emissions decreased by 6.8%. This was caused by the decline in road traf-fic, especially of heavy duty vehicles and passenger cars. In 2018 53% of the total nitrogen ox-ides emissions originate from road transport (including fuel exports).

Main sources and emission trends in Austria As can be seen in Figure 9 and Table 46, the main source for NOx emissions in Austria with a share of 93% in 2018 are 1.A Fuel Combustion Activities. Sector 3 Agriculture contributes with 7.1%.

NFR sectors 2 Industrial Processes and Product Use and 5 Waste are minor sources regarding NOx emissions. These sectors contribute with 0.3% and 0.01% to national total NOx emissions in 2018.

Note: NOx emissions from NFR sector 1.B Fugitive Emissions from fuels are reported as IE.

Figure 9: Share of NFR sectors 2018 in NOx emissions.


Within source category 1.A Fuel Combustion Activities, 1.A.3.b Road Transportation, with about 53% of national total emissions in 2018, is the main contributor to total NOx emissions.

Please note that emissions from mobile sources are calculated based on fuel sold, which is higher than fuel used because of the high extent of fuel export in 1.A.3 Transport since the 1990ies: Emissions for 2018 based on fuel used amount to 136 kt and are about 15 kt lower than based on fuel sold (see also chapter 2.5).

The most important NOx sources within NFR 1.A Fuel Combustion Activities are: NFR 1.A.3 Transport – in particular diesel-powered passenger cars and heavy duty traffic. In

passenger transport the number of diesel vehicles has rapidly increased since the 1990ies. Also mileage has increased in passenger and freight transport. While NMVOC and CO emis-

92,6%

0,3% 7,1% 0,01%

Share of NFR sectors 2018 – NOx emissions




3 AGRICULTURE

5 WASTE




sions from road transport have been reduced significantly since 1990 due to well-functioning after-treatment devices, NOx emissions increased up to 2005. Since then NOx emissions have shown a decreasing trend, which is due to a combination of several facts. First of all, NOx emissions from gasoline passenger cars are declining and are negligible now; second, NOx emissions from heavy duty vehicles have decreased significantly due to the above men-tioned well-functioning after-treatment devices (SCR, EGR). Additionally, NOx emissions from fuel export show a decreasing trend because of the rapid renewal rate of the transit fleet and the associated decrease in specific emissions per vehicle kilometer. Nevertheless the specific emissions of the diesel passenger car fleet will only decrease when the fleet penetration of the new vehicles (Euro 6d_temp) continues.

NFR 1.A.2 Manufacturing Industries and Construction- NOx emissions have decreased com-pared to 1990 (-20%) mainly caused by increased efficiency, implementation/installation of denitrification installations (SCR/SNCR) and/or low-NOx burners, introduction of modern fuel technology, gas-fired equipment and furnaces. This is counterbalanced by a significant in-crease in energy consumption (also the use of biomass).

NFR 1.A.4 Other Sectors (mainly residential heating): NOx emissions decreased steadily be-tween 1990 and 2018 (-37%) mainly due to increased efficiency and modern fuel technology. From 2017 to 2018 NOx emissions of this source category decreased by 7.1% because of lower emissions from residential heating, due to warmer weather.

3 Agriculture

Besides the main NOx emitter NFR sector 1.A Fuel Combustion Activities, sector 3 Agriculture is also a source of NOx emissions in Austria, although to a much lesser extent. It is responsible for 7.1% of national total NOx emissions in Austria in 2018. Within the Agriculture sector, source category 3.D Agricultural Soils is the biggest contributor with 95% in 2018. Emissions mainly re-sult from the application of N-fertilizers and organic waste (largely animal manure) on agricultur-al soils.

Since 1990 the agricultural NOx emissions decreased by 11%, mainly influenced by livestock numbers and N-fertilizer consumption. Compared to the previous year 2017 emissions slightly decreased by 2.1%, which was due to reduced mineral fertilizer consumption.

Figure 10: NOx emissions in Austria 1990–2018 by sectors in absolute terms.

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NO

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NOx emissions in Austria 1990 – 2018 NFR by sectors

5 WASTE

3 AGRICULTURE



1.A.5 Other

1.A.4 Other Sectors

1.A.3 Transport






Table 46: NOx emissions per NFR Category 1990 and 2018, trend 1990–2018 and share in total emissions.

NFR Category NOx Emission in [kt]

Trend Share in National Total

1990 2018 1990– 2018

2017–2018

1990 2018

1 ENERGY 200.79 139.68 -30% -7% 92% 93%


1.A.1 Energy Industries 17.82 10.66 -40% -9% 8% 7%



1.A.1.c Manufacture of Solid fuels & Other Energy Ind. 1.37 0.65 -53% -8% 1% <1%


1.A.2.a Iron and Steel 5.41 3.57 -34% -4% 2% 2%

1.A.2.b Non-ferrous Metals 0.25 0.26 4% 11% <1% <1%

1.A.2.c Chemicals 1.69 1.39 -18% -13% 1% 1%

1.A.2.d Pulp, Paper and Print 7.17 4.41 -38% 3% 3% 3%

1.A.2.e Food Processing, Beverages & Tobacco 1.74 0.68 -61% -4% 1% <1%


1.A.2.g Manufacturing Industries and Constr. - other 6.77 10.22 51% -4% 3% 7%

1.A.3 Transport 120.02 83.80 -30% -8% 55% 56%

1.A.3.a Civil Aviation 0.41 1.62 297% 10% <1% 1%

1.A.3.b Road Transportation 116.60 80.65 -31% -8% 54% 53%

1.A.3.c Railways 1.82 0.74 -59% -22% 1% <1%

1.A.3.d Navigation 0.58 0.44 -24% -26% <1% <1%

1.A.3.e Other transportation 0.61 0.35 -42% -20% <1% <1%

1.A.4 Other Sectors 29.85 18.82 -37% -7% 14% 12%


1.A.4.b Residential 16.22 10.68 -34% -9% 7% 7%


1.A.5 Other 0.07 0.08 11% <1% <1% <1%

1.B FUGITIVE EMISSIONS FROM FUELS IE IE IE IE IE IE

2 INDUSTRIAL PROCESSES /PRODUCT USE 4.27 0.41 -90% -13% 2% <1%


2.B CHEMICAL INDUSTRY 4.07 0.28 -93% -18% 2% <1%

2.C METAL PRODUCTION 0.17 0.11 -34% 1% <1% <1%







2.L Other production, consumption, storage … NO NO NO NO NO NO

3 AGRICULTURE 12.05 10.75 -11% -2% 6% 7%

3.B MANURE MANAGEMENT 0.60 0.55 -8% <1% <1% <1%

3.D AGRICULTURAL SOILS 11.40 10.18 -11% -2% 5% 7%

3.F FIELD BURNING OF AGRICULTURAL RESIDUE 0.05 0.02 -58% -1% <1% <1%

3.I Agriculture OTHER NO NO NO NO NO NO

5 WASTE 0.10 0.02 -82% 2% <1% <1%

Total without sinks 217.22 150.86 -31% -6.8%



2.1.3 NMVOC Emissions

In 1990, national total NMVOC emissions amounted to 334 kt. Emissions have decreased steadily since then and in the year 2018 emissions were reduced by 68% to 107 kt compared to 1990. The largest reductions were achieved in the road transport sector due to an increased use of catalytic converters and diesel cars. Reductions in the solvent sector were due to several regulations (Solvent Ordinance, Cogeneration Act, VOC Emissions Ordinance). From 2017 to 2018 emissions decreased by 3.2%.

Main sources and emission trends in Austria As can be seen in Figure 11 and Table 47, the main sources of NMVOC emissions in 2018 in Austria are NFR sectors 3 Agriculture with a contribution of 34%, 1.A Fuel Combustion Activities with a contribution of 32% and 2 Industrial Processes and Product Use with a share of 31% in national total emissions.

NMVOC emissions resulting from NFR sectors 1.B Fugitive Emissions and 5 Waste are minor sources contributing to national total NMVOC emissions with 2.0% and 0.1%, respectively.

Figure 11: Share of NFR sectors 2018 in NMVOC emissions.

3 Agriculture Within NFR sector 3 Agriculture, the largest part of NMVOC emissions stems from NFR subcat-egory 3.B Manure Management (73%). Smaller amounts arise from NFR subcategory 3.D Agri-cultural Soils (27%) and source category 3.F Field burning of agricultural residues is negligible with 0.02%. NFR 3.B Manure Management: The NMVOC emission trend is related to livestock numbers

and feeding situation (silage and non-silage feeding) and shows a decrease of 24% between 1990 and 2018. Compared to the previous year 2017 emissions decreased by 1.0%. Within this source category manure management of cattle has the highest contribution with 90%.

NFR 3.D Agricultural Soils: Emissions arise from animal manure spread on agricultural soils (3.D.a.2.a), grazing animals (3.D.a.3) and cultivated crops (3.D.e). The falling emission trend since 1990 by 40% is mainly driven by the reduced livestock numbers resulting in smaller amounts of NMVOC that is applied to agricultural soils.

32,1%

2,0%

31,4%

34,5%

0,1% Share of NFR sectors 2018 – NMVOC emissions




3 AGRICULTURE

5 WASTE




1.A Fuel Combustion Activities NMVOC emissions from 1.A Fuel Combustion Activities contribute with 32% to the national to-tal. Within sector 1.A Fuel Combustion Activities the main emitters in 2018 are 1.A.4 Other Sec-tors (26% of the national total, mainly residential heating) and 1.A.3 Transport (5.2% of the na-tional total). In source category 1.A Fuel Combustion Activities, NMVOC emissions decreased notably in both main categories: NFR 1.A.4 Other Sectors: NMVOC emissions from residential heating decreased by 43%

since 1990 mainly due to the strong decrease in coal consumption but also due to improved bi-omass heating in households. Compared to the previous year 2017 emissions from this source category decreased by 7.7% in 2018 mainly due to the warm weather.

NFR 1.A.3 Transport: The introduction of more stringent emission standards for passenger cars according to the state-of-art (regulated catalytic converter) and the increased use of die-sel vehicles in the passenger car sector are drivers for the decreasing trend since 1990 of NMVOC emissions (-94%).


The main source of NMVOC emissions in Austria within sector 2 Industrial Processes and Product Use is NFR 2.D.3 Solvent Use (28% of the national total).

The overall reduction in sector Solvent Use is due to abatement measures such as substitution, using products with lower solvent content as well as exhaust gas cleaning systems and after treatment as a result of legal requirements. NFR 2.D.3.a Domestic Solvent use including fungicides: The increase of the NMVOC emis-

sions until 2000 in this category is due to an increased use of solvent containing products in households; from 2000 onwards are based on surveys regarding the solvent contents in the early 2000s and another in 2015, which showed that solvent contents were decreasing due to legal and technical measures.

NFR 2.D.3.d Coating Application: This category contributed mainly to the overall decrease in the emissions of the concerned sector, which was primarily achieved from 1990 to 2000 due to various legal and regulatory enforcements (especially for coil and wood coating until 1999) and due to a reduction of solvents in paint as well as due to the substitution of solvent-based paint for paint with less or without solvents, due to the paints directive (see Chapter 4.5).

NFR 2.D.3.e and 2.D.3.f Degreasing and Dry Cleaning: The emission reduction in this sub sectors was achieved due to technical abatement measures such as closed loop processes, waste gas purification and recycling.

NFR 2.D.3.g Chemical Products: An emission reduction of 81% between 1990 and 2018 could be achieved due to technical abatement measures such as closed loop processes, waste gas purification and recycling but also due to product substitution. The NFR 2.D.3.g covers manufacturing activities mainly of pharmaceutical products, paints, wood preserva-tives and glues.

NFR 2.D.3.h Printing: The decrease of NMVOC emissions (-70% between 1990 and 2018) is a result of legal/abatement measures.

NFR 2.D.3.i Other solvent use: The significant long term emission reduction of 91% could be achieved due to technical abatement measures such as closed loop processes, waste gas pu-rification and recycling.



Figure 12: NMVOC emissions in Austria 1990–2018 by sectors in absolute terms.

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35019

9019

9119

9219

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NM

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NMVOC emissions in Austria 1990 – 2018 by NFR sectors

3 AGRICULTURE



1.A.5 Other

1.A.4 Other Sectors

1.A.3 Transport






Table 47: NMVOC emissions per NFR Category 1990 and 2018, trend 1990–2018 and share in total emissions.

NFR Category NMVOC Emission in [kt]


1990 2018 1990–2018

2017–2018

1990 2018

1 ENERGY 163.13 36.56 -78% -7% 49% 34%


1.A.1 Energy Industries 0.32 0.31 <1% -6% <1% <1%


1.A.3 Transport 97.78 5.62 -94% -6% 29% 5%

1.A.3.a Civil Aviation 0.20 0.21 1% 11% <1% <1%

1.A.3.b Road Transportation 96.62 5.11 -95% -6% 29% 5%

1.A.3.c Railways 0.37 0.07 -80% -22% <1% <1%

1.A.3.d Navigation 0.59 0.23 -61% -12% <1% <1%


1.A.4 Other Sectors 47.85 27.40 -43% -8% 14% 26%

1.A.4.a Commercial/Institutional 1.34 0.59 -56% <1% <1% 1%

1.A.4.b Residential 40.84 24.21 -41% -8% 12% 23%


1.A.5 Other 0.01 0.02 24% 6% <1% <1%

1.B FUGITIVE EMISSIONS FROM FUELS 15.49 2.17 -86% -5% 5% 2%


118.54 33.63 -72% -1% 35% 31%


2.B CHEMICAL INDUSTRY 1.62 0.27 -83% -15% <1% <1%

2.C METAL PRODUCTION 0.51 0.47 -9% 2% <1% <1%

2.D NON ENERGY PRODUCTS/ SOLVENTS 114.44 30.13 -74% -1% 34% 28%

2.D.3 Solvent use 114.44 30.13 -74% -1% 34% 28%

2.D.3.a Domestic solvent use including fungicides 16.30 16.10 -1% -1% 5% 15%

2.D.3.b Road paving with asphalt 0.01 0.02 273% 11% <1% <1%

2.D.3.c Asphalt roofing NE NE NE NE NE NE

2.D.3.d Coating applications 45.79 5.31 -88% -1% 14% 5%

2.D.3.e Degreasing 13.26 1.33 -90% -1% 4% 1%

2.D.3.f Dry cleaning 0.44 0.05 -89% -1% <1% <1%

2.D.3.g Chemical products 12.79 2.38 -81% -1% 4% 2%

2.D.3.h Printing 12.65 3.74 -70% -1% 4% 3%

2.D.3.i Other solvent use 13.20 1.20 -91% -1% 4% 1%


2.H Other Processes 1.89 2.71 43% 2% 1% 3%




2.L Other production, consumption, storage, … NO NO NO NO NO NO

3 AGRICULTURE 52.19 36.97 -29% -1% 16% 34%

3.B MANURE MANAGEMENT 35.42 26.94 -24% -1% 11% 25%


3.F FIELD BURNING OF AGRICULTURAL RES. 0.06 0.01 -86% -6% <1% <1%


5 WASTE 0.16 0.06 -64% -5% <1% <1%




2.1.4 NH3 Emissions

In 1990, national total NH3 emissions amounted to 62 kt; emissions have increased over the pe-riod from 1990 to 2018. In 2018, emissions were 4.7% above 1990 levels and amounted to 65 kt. NH3 in Austria is almost exclusively emitted in the agricultural sector. The higher NH3 emis-sions (in spite of a decrease in the number of cattle) can be explained by an increase in loose housing systems (to ensure animal welfare and according to EU law) and an increase of high-capacity dairy cows. Additionally, there has been an increase in the use of urea as nitrogen fer-tiliser (a cost-efficient but otherwise less efficient fertiliser). Compared to the previous year, emissions in 2018 decreased by 1.6%. The main reason is the lower amount of mineral fertiliz-er, in particular urea, which was applied on agricultural soils. Furthermore, the livestock num-bers of cattle (dairy cows and other cattle) and swine were falling. However, increased N excre-tion due to increased milk yields counterbalanced the decreasing dairy cow number.

Main sources and emission trends in Austria

As it is illustrated in Figure 13 and in Table 48, NH3 emissions in Austria are almost exclusively emitted by the agricultural sector. The share in national total NH3 emissions is about 93% for 2018. Sector 1.A Fuel Combustion Activities contributes with 3.9% in national total emissions. NH3 emissions resulting from NFR sectors 2 Industrial Processes and Product Use and 5 Waste are minor sources. These sectors contribute to national total NH3 emissions in 2018 with 0.2% and 2.5%, respectively.

Figure 13: Share of NFR sectors 2018 in NH3 emissions.

3 Agriculture

In 1990 national NH3 emissions from the sector Agriculture amounted to 59 kt; emissions have increased by 2.2% since then and by the year 2018 they amounted to 60 kt. The reason for this increase is, as already explained above, due to an increase in loose-housing systems and high-capacity dairy cows. Furthermore, there was a higher consumption of urea as nitrogen fertilizer. Compared to the previous year, emissions decreased in 2018 (-1.5%), because of the lower amount of mineral fertilizer, in particular urea, which was applied on agricultural soils. Further-more, the livestock numbers of cattle (dairy cows and other cattle) and swine were falling. How-ever, the decrease of dairy cows was compensated with the rising milk yield.

3,9% 0,2%

93,4%

2,5%

Share of NFR sectors 2018 ‒ NH3 emissions




3 AGRICULTURE

5 WASTE




NFR 3.B Manure Management has a share of 45% in national total NH3 emissions in 2018. The emissions result from animal husbandry and the storage of manure. Within this source category manure management of cattle has the highest contribution with 62%. Emissions are linked to livestock numbers but also to housing systems and manure treatment (e.g. NH3 emissions from loose housing systems are considerable higher than those applied for tied systems). Since 1990 emissions from this sub sector are increasing by 12%, mainly due to higher emissions from cattle.

NFR 3.D Agricultural Soils with a share of 48% has the highest contribution to national total NH3 emissions in 2018. These emissions result from fertilization with mineral N-fertilizers as well as organic fertilizers (including the application of animal manure, sewage sludge, energy crops and compost). Another source of NH3 emissions is urine and dung deposited on pas-tures by grazing animals.


NH3 emissions from 1.A Fuel Combustion Activities are the second largest source category alt-hough it is only a small source of NH3 emissions with a contribution to national total NH3 emis-sions of 3.9% in 2018. NH3 emissions from NFR sector 1.A are increasing: in 1990, emissions amounted to about 2.0 kt. In the year 2018, they were about 29% higher than 1990 levels and amounted to about 2.5 kt. The rise is mainly due to increased emissions from 1.A.3.b.i Passen-ger Cars ‒ 4 stroke engines and an increase of biomass use in category 1.A.1.a Public Electrici-ty and Heat.

Figure 14: NH3 emissions in Austria 1990–2018 by sectors in absolute terms.

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NH3 emissions in Austria 1990 ‒ 2018 by NFR sectors

5 WASTE

3 AGRICULTURE



1.A.5 Other

1.A.4 Other Sectors

1.A.3 Transport






Table 48: NH3 emissions per NFR Category 1990 and 2018, trend 1990–2018 and share in total emissions.

NFR Category NH3 Emission in [kt]


1990 2018 1990–2018

2017–2018

1990 2018

1 ENERGY 1.96 2.54 29% -2% 3% 4%

1.A FUEL COMBUSTION ACTIVITIES 1.96 2.54 29% -2% 3% 4%

1.A.1 Energy Industries 0.20 0.43 118% -6% <1% 1%

1.A.2 Manufacturing Industries and Construction 0.33 0.41 22% 7% 1% 1%

1.A.3 Transport 0.80 1.12 39% <1% 1% 2%

1.A.4 Other Sectors 0.63 0.58 -7% -9% 1% 1%

1.A.5 Other 0.00 0.00 38% 1% <1% <1%

1.B FUGITIVE EMISSIONS FROM FUELS IE 0.00 164% <1%


0.34 0.14 -60% -19% 1% <1%



2.C METAL PRODUCTION IE IE IE IE IE IE








3 AGRICULTURE 59.06 60.36 2% -2% 96% 93%

3.B MANURE MANAGEMENT 26.05 29.12 12% -1% 42% 45%

3.B.1 Cattle 13.89 17.92 29% -1% 23% 28%

3.B.2 Sheep 0.74 0.98 31% 1% 1% 2%

3.B.3 Swine 8.47 5.69 -33% -2% 14% 9%

3.B.4 Other livestock 2.94 4.54 54% 0% 5% 7%

3.B.4.a Buffalo NO NO NO NO NO NO

3.B.4.d Goats 0.11 0.28 145% <1% <1% <1%

3.B.4.e Horses 0.65 1.72 164% <1% 1% 3%

3.B.4.f Mules and asses IE IE IE IE IE IE

3.B.4.g Poultry 2.15 2.50 17% <1% 3% 4%

3.B.4.h Other animals 0.03 0.03 11% <1% <1% <1%


3.D.a Direct Soil Emissions 32.98 31.22 -5% -2% 53% 48%

3.D.b Indirect emissions from managed soils NO NO NO NO NO NO

3.D.c On-farm storage NA NA NA NA NA NA

3.D.d Off-farm storage NA NA NA NA NA NA

3.D.e Cultivated crops NA NA NA NA NA NA

3.D.f Use of pesticides NA NA NA NA NA NA

3.F FIELD BURNING OF AGRICULTURAL RES. 0.04 0.01 -71% -1% <1% <1%


5 WASTE 0.37 1.60 336% <1% 1% 2%

Total without sinks 61.73 64.63 5% -2%



2.1.5 Carbon monoxide (CO) Emissions

CO is a colourless and odourless gas, formed when carbon in fuel is not burned completely. It is a component of motor vehicle exhaust; other sources of CO emissions include industrial pro-cesses, non-transportation fuel combustion, and natural sources such as wildfires.

In 1990, national total CO emissions amounted to 1 249 kt. Emissions considerably decreased from 1990 to 2018. In 2018, emissions were 61% below 1990 levels and amounted to 490 kt. This reduction was mainly due to decreasing emissions from road transport (catalytic converters). The emissions decreased between 2017 and 2018 by 7.4%, mainly due to sectors iron and steel and residential (stationary).


As can be seen in Figure 15 and Table 49, CO emissions in Austria are almost exclusively emit-ted by the Energy sector, and more specifically, 1.A Fuel Combustion Activities. The share in national total CO emissions is about 96% for 1990 and for 2018.

CO emissions resulting from NFR sectors 2 Industrial Processes and Product Use, 3 Agriculture and 5 Waste are minor sources. These sectors contribute to national total CO emissions with 2.9%, 0.1% and 0.6%, respectively.

Note: CO emissions from NFR sector 1.B Fugitive Emissions from fuels are reported as IE.

Figure 15: Share of NFR sectors 2018 in CO emissions.

1.A Fuel Combustion Activities As described above, in the period 1990–2018, the share of CO emissions from 1.A Fuel Com-bustion Activities in national total emissions has been quite stable in spite of growing activities because of considerable efforts regarding abatement techniques and improved combustion effi-ciency in all sub-sectors.

The main contributors of CO emissions within sector 1.A Fuel Combustion Activities are: NFR 1.A.4 Other Sectors: CO emissions decreased since 1990 by 41% due to the switch-

over to improved technologies and decreased use of coke. Between 2017 and 2018 emis-sions decreased by 7.8% mainly due to the warm weather.

96,4%

2,9% 0,1% 0,6%

Share of NFR sectors 2018 ‒ CO emissions




3 AGRICULTURE

5 WASTE




NFR 1.A.2 Manufacturing Industries and Construction: Compared to 1990 emissions de-creased by 36%. The trend is dominated by fuel combustion from iron and steel industry. The emissions decrease of 8.8% compared to the previous year 2017 is also mainly due to lower emissions from the sector iron and steel.

NFR 1.A.3 Transport: The significant emission reduction of 87% from 1.A.3 Transport com-pared to 1990 was mainly possible due to optimized combustion processes in the engine and the introduction of the catalytic converters.

Figure 16: CO emissions in Austria 1990–2018 by sectors in absolute terms.

0

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1400

1990

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em

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CO emissions in Austria 1990 ‒ 2018 by NFR sectors

5 WASTE

3 AGRICULTURE



1.A.5 Other

1.A.4 Other Sectors

1.A.3 Transport






Table 49: CO emissions per NFR Category 1990 and 2018, trend 1990–2018 and share in total emissions.

NFR Category CO Emission in [kt]


1990 2018 1990–2018

2017–2018

1990 2018

1 ENERGY 1200.68 472.56 -61% -8% 96% 96% 1.A FUEL COMBUSTION ACTIVITIES 1200.68 472.56 -61% -8% 96% 96% 1.A.1 Energy Industries 6.10 4.27 -30% -7% <1% 1% 1.A.2 Manufacturing Industries and Construction 231.22 147.59 -36% -9% 19% 30% 1.A.2.a Iron and Steel 210.72 133.30 -37% -8% 17% 27% 1.A.2.b Non-ferrous Metals 0.05 0.05 2% 1% <1% <1% 1.A.2.c Chemicals 0.46 0.49 6% -23% <1% <1% 1.A.2.d Pulp, Paper and Print 4.15 2.01 -52% 5% <1% <1% 1.A.2.e Food Processing, Beverages and Tobacco 0.20 0.12 -41% -1% <1% <1% 1.A.2.f Non-metallic Minerals 11.03 5.71 -48% -29% 1% 1% 1.A.2.g Manufacturing Industries and Constr. - other 4.61 5.91 28% -2% <1% 1% 1.A.3 Transport 537.13 68.77 -87% -4% 43% 14% 1.A.3.a Civil Aviation 2.47 3.96 60% 1% <1% 1% 1.A.3.b Road Transportation 529.40 62.20 -88% -4% 42% 13% 1.A.3.c Railways 2.04 0.50 -75% -21% <1% <1% 1.A.3.d Navigation 3.19 2.00 -37% -5% <1% <1% 1.A.3.e Other transportation 0.04 0.11 162% -7% <1% <1% 1.A.4 Other Sectors 426.00 251.64 -41% -8% 34% 51% 1.A.4.a Commercial/Institutional 11.76 3.93 -67% -4% 1% 1% 1.A.4.b Residential 379.98 229.53 -40% -8% 30% 47% 1.A.4.c Agriculture/Forestry/Fisheries 34.27 18.19 -47% -6% 3% 4% 1.A.5 Other 0.22 0.30 37% 1% <1% <1% 1.B FUGITIVE EMISSIONS FROM FUELS IE IE IE IE IE IE 2 INDUSTRIAL PROCESSES AND PRODUCT

USE 37.19 14.22 -62% 1% 3% 3%

2.A MINERAL PRODUCTS IE IE IE IE IE IE 2.B CHEMICAL INDUSTRY 12.67 11.13 -12% <1% 1% 2% 2.C METAL PRODUCTION 23.32 2.09 -91% 4% 2% <1% 2.D NON ENERGY PRODUCTS/ SOLVENTS 0.27 0.27 <1% <1% <1% <1% 2.G Other product manufacture and use 0.94 0.73 -23% -4% <1% <1% 2.H Other Processes NA NA NA NA NA NA 2.I Wood processing NA NA NA NA NA NA 2.J Production of POPs NO NO NO NO NO NO 2.K "Consumption of POPs and heavy metals NO NO NO NO NO NO 2.L Other production, consumption, storage, … NO NO NO NO NO NO 3 AGRICULTURE 1.23 0.35 -72% -2% <1% <1% 3.B MANURE MANAGEMENT NA NA NA NA NA NA 3.D AGRICULTURAL SOILS NA NA NA NA NA NA 3.F FIELD BURNING OF AGRICULT. RESIDUES 1.23 0.35 -72% -2% <1% <1% 3.I AGRICULTURE OTHER NO NO NO NO NO NO 5 WASTE 10.31 2.96 -71% -6% 1% 1% 5.A SOLID WASTE DISPOSAL ON LAND 10.26 2.94 -71% -6% 1% 1% 5.B BIOLOGICAL TREATMENT OF WASTE NA NA NA NA NA NA 5.C INCINERATION/BURNING OF WASTE 0.05 0.02 -67% 4% <1% <1% 5.D WASTEWATER TREATMENT NA NA NA NA NA NA 5.E OTHER WASTE NE NE NE NE NE NE Total without sinks 1249.41 490.09 -61% -7%



2.2 Emission Trends for Particulate matter (PM)

Particulate matter (PM) is a complex mixture consisting of both directly emitted and secondarily formed components of both natural and anthropogenic origin (e.g. geological material, combustion by-products and biological material). It has an inhomogeneous composition of sulphate, nitrate, ammonium, organic carbon, heavy metals, PAH and dioxins/furans (PCDD/F). Anthropogenic PM is formed during industrial production and combustion processes as well as during mechani-cal processes such as abrasion of surface materials. In addition, PM originates from secondary formation from SO2, NOx, NMVOC or NH3.

PM does not only have effects on the chemical composition and reactivity of the atmosphere but also affects human and animal health and welfare. When breathed in, a particle-loaded atmos-phere impacts on the respiratory tract. The observable effects are dependent on the particle size, therefore for legislative issues particulate matter is classified according to its size (see Figure 17).

PM10 is the fraction of suspended particulate matter in the air with an aerodynamic diameter of less than 10 μm. These particles are small enough to be breathable and could be deposited in lungs, which may cause deteriorated lung functions.

The size fraction PM2.5 refers to particles with an aerodynamic diameter of less 2.5 μm. Studies link long-term exposure to PM2.5 with cardiovascular and respiratory deaths, as well as in-creased sickness, such as childhood respiratory diseases. PM2.5 also causes reductions in visi-bility and solar radiation due to enhanced scattering of light. Aerosol precursors such as ammo-nia (the source of which is mainly agriculture) form PM2.5 as secondary particles through chemi-cal reactions in the atmosphere.

Total suspended particulate matter (TSP) refers to the entire range of ambient air matter that can be collected, from the sub-micron level up to 100 μm in aerodynamic diameter (dae). Particles with a dae larger than 100 μm will not remain suspended in the atmosphere for a significant length of time. Compared to PM10 and PM2.5, TSP remains in the air for shorter periods of time and is therefore generally not carried over long distances. As a result, TSP pollution tends to be a local rather than a regional problem, occurring close to industrial sources, such as metal processing plants and mining operations, along roads because of the re-suspension, and close to stables and agricultural crop land.

Figure 17: Distribution of TSP, PM10 and PM2.5 (schematic).


Particulate matter emissions in Austria mainly arise from 1.A Fuel Combustion Activities (1.A.3 Road transport, 1.A.4 Other sectors – residential heating), 2 Industrial Processes and Product Use and 3 Agriculture. Where for TSP the most important source is the sector 2.A.5 Mining, con-struction/demolition and handling of products, small heating installations are the highest contributor for PM2,5 emissions.

PM2.5 PM10 TSP






NFR sectors 1.B Fugitive Emissions and 5 Waste are minor sources regarding PM emissions (less than 2%).

Figure 18: Share of NFR sectors 2018 in PM emissions (TSP, PM10 and PM2.5).

Table 50: National total emissions and emission trends for particulate matter (PM) 1990–2018.

Year Emissions [kt] TSP PM10 PM2.5

1990 53.21 40.90 27.17

: NR NR NR

1995 52.06 39.37 25.69

: NR NR NR

2000 50.58 37.82 24.12

2001 50.26 37.80 24.38

2002 49.17 36.74 23.56

2003 48.81 36.48 23.39

44,5%

1,0%

40,9%

11,9%

1,8%

Share of NFR sectors 2018 - TSP emissions

53,1%

0,7%

29,8%

14,8% 1,6%

Share of NFR sectors 2018 - PM10 emissions

83,7%

0,4%

12,1% 1,9% 1,9%

Share of NFR sectors 2018 - PM2.5 emissions




3 AGRICULTURE

5 WASTE




Year Emissions [kt] TSP PM10 PM2.5

2004 48.81 36.18 22.83

2005 48.14 35.77 22.67

2006 46.74 34.78 22.17

2007 45.67 33.78 21.35

2008 45.57 33.23 20.44

2009 43.14 31.48 19.27

2010 43.77 32.08 19.87

2011 43.01 31.12 18.73

2012 42.26 30.51 18.27

2013 41.62 29.89 17.69

2014 40.25 28.35 16.11

2015 39.81 28.02 15.94

2016 39.43 27.62 15.56

2017 39.69 27.58 15.30

2018 38.32 26.40 14.26

Trend 1990–2018 -28.0% -35.5% -47.5%

Particulate matter (PM) emissions show a decreasing trend over the period 1990 to 2018: TSP emissions decreased by 28%, PM10 emissions were about 35% below the level of 1990, and PM2.5 emissions dropped by about 48%. Between 2017 and 2018 PM10, PM2.5 and TSP emissions de-creased by 4.3% (PM10), 6.8% (PM2.5) and 3.4% (TSP). The decrease of TSP, PM10 and PM2.5

was mainly because of reductions in the sector 1 A 4 b 1 residential: stationary, due to the mild weather in 2018 and a decrease in the use of biomass for heating. To a small extent, the latest decline can also be explained by efficiency improvements through thermal renovation and by a switch to modern biomass boilers and stoves (improvements in fuel combustion technologies). TSP emissions also decreased slightly due to reduced emissions from 2.A.5.a Quarrying and min-ing of minerals other than coal.

1.A Fuel Combustion Activities One of the main sources of PM emissions is NFR sector 1.A Fuel Combustion Activities. Within this source the largest contributors are NFR 1.A.4 Other Sectors, NFR 1.A.3 Transport, NFR 1.A.1 Energy Industries and NFR 1.A.2 Manufacturing Industries and Construction. Further im-portant sources of PM emissions are the sectors 2 Industrial Processes and Product Use (2.A Mineral Products) as well as 3 Agriculture (3.D Agricultural Soils). NFR 1.A.4 Other Sectors: small combustion plants, residential heating, household ovens and

stoves (NFR 1.A.4.b) are large sources of TSP, PM10 and PM2.5, as well as Off Road Vehicles and Other Machinery (NFR 1.A.4.c) which are important sources of PM2.5. Emission reduction could be achieved through: substitution of old installations with modern technology, reduction of biomass consumption in household ovens and stoves due to less use as a main

heating system, installation of energy-saving boilers, connection to the district-heating networks or other public energy- and heating networks,





substitution from high-emission fuels to low-emission (low-ash) fuels (wood pellets), raising awareness for energy saving.

This downward trend counteracted the application of CO2-neutral fuels such as biomass (wood, pellets etc.).

NFR 1.A.3 Transport includes transportation activities, mechanical abrasion from tyres, brakes and road surfaces and has a contribution of 18% TSP, 17% PM10 and 21% PM2.5 emissions of the respective national totals. The reduction of PM emissions since 2005 is due to improvements in the drive and exhaust gas after treatment technologies and the integra-tion of particulate filter systems in the fuel consumption based taxation for passenger cars in Austria (NOVA). PM emissions from automobile tyre and break wear (NFR sector 1.A.3.b.6) and road abrasion (NFR 1.A.3.b.7) are increasing as a function of travelled vehicles kilome-tres which have shown an increasing trend since 1990.

NFR 1.A.1 Energy Industries and NFR 1.A.2 Manufacturing Industries and Construction: NFR 1.A.2 Manufacturing Industries and Construction is responsible for 2.6% of the national total TSP emissions, 3.5% of PM10 emissions and 5.5% of PM2.5 emissions. 1.A.1 Energy Indus-tries contributes in 2018 with 3.2% of TSP, 4.2% of PM10 and 6.7% of PM2.5 to the respective national totals. Achievements for reducing emissions in both subcategories were made by sev-eral appropriate measures in this category: application of abatement techniques such as flue gas collection and flue gas cleaning sys-

tems (already in the 1980), installation of energy- and resource-saving production processes (already in the 1980), substitution from high-emission fuels to low-emission (low-ash) fuels (already in the 1980), raising awareness for environmental production.

While emissions in category 1.A.2 have decreased due to these measures, they have in-creased in 1.A.1 by the increases in energy consumption. A reason for rising PM emissions in these source categories is the increasing use of CO2-neutral fuels such as biomass (wood, pellets etc.) in district-heating plants. Even with modern combustion technology, solid bio-mass causes considerable higher emissions than liquid or gaseous fuels.


NFR 2.A Mineral Products: The handling of bulk materials like mineral products and the activ-ities in the field of civil engineering represent the majority of PM sources within sector 2 In-dustrial Processes and Product Use. The increase of PM emissions since 1990 of subcatego-ry NFR 2.A Mineral products is a result of increased activities due to manifold construction activities, whereas from 2008 to 2010 a decrease because of the economic crisis can be not-ed. Since 2011 the emission trend shows ups and downs. Between 2017 and 2018 a decrease can be observed.

NFR 2.C Metal Production, a decreasing trend of about 89% of all PM fractions can be noted for the period 1990 to 2018 because considerable efforts were made by introducing low-PM technologies, abatement techniques, flue gas collection and flue gas cleaning systems etc. In 2018 this sub category represents a minor source of PM emissions.

3 Agriculture NFR 3.D Agricultural Soils, which consider tillage operations and harvesting activities, is the

main source of PM emissions within sector Agriculture. The decrease in agricultural produc-tion (soil cultivation, harvesting etc.) is responsible for the decrease since 1990 of about 3.5% of the agricultural PM2.5 emissions from this source category. TSP and PM10 emissions from 3.D Agricultural Soils decreased by 5.5% and 5.8% over the period 1990 to 2018.



NFR 3.B Manure Management comprises PM emissions from animal husbandry, primary connected with the manipulation of forage and a smaller part arises from dispersed excre-ments and litter. Between 1990 and 2018 emissions decreased by 11% for all PM fractions due to falling livestock numbers. Compared to the previous year emissions decreased by 0.9%.

PM10 emissions and emission trends in Austria

National total PM10 emissions amounted to 41 kt in 1990 and have decreased steadily so that by the year 2018 emissions were reduced by 35% (to 26 kt) – see Table 51.

As shown in Figure 18 and Table 51, the main sources for PM10 emissions in 2018 in Austria are combustion processes in the NFR category 1.A Fuel Combustion Activities (53% in national total emissions) as well as handling of bulk materials like mineral products and the activities in the field of civil engineering of category 2 Industrial Processes and Product Use (30% in nation-al total emissions). Sector 3 Agriculture contributes with a share of 15% in national total PM10 emissions.

Figure 19: PM10 emissions in Austria 1990–2018 by sectors in absolute terms.

0

5

10

15

20

25

30

35

40

45

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

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2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

PM10

em

issi

ons

[kt]

PM10 emissions in Austria 1990 ‒ 2018 by NFR sectors

5 WASTE

3 AGRICULTURE



1.A.5 Other

1.A.4 Other Sectors

1.A.3 Transport






Table 51: PM10 emissions per NFR Category 1990 and 2018, trend 1990–2018 and share in total emissions.

NFR Category PM10 Emission in [kt] Trend Share in National Total

1990 2018 1990– 2018

2017– 2018

1990 2018

1 ENERGY 25.22 14.21 -44% -6% 62% 54% 1.A FUEL COMBUSTION ACTIVITIES 24.82 14.03 -43% -6% 61% 53% 1.A.1 Energy Industries 1.00 1.12 12% -4% 2% 4% 1.A.2 Manufacturing Industries and Construction 2.18 0.92 -58% -10% 5% 3% 1.A.2.a Iron and Steel 0.05 0.01 -78% -7% <1% <1% 1.A.2.b Non-ferrous Metals 0.01 0.01 -21% 2% <1% <1% 1.A.2.c Chemicals 0.21 0.21 -1% -18% 1% 1% 1.A.2.d Pulp, Paper and Print 0.95 0.21 -78% 2% 2% 1% 1.A.2.e Food Processing, Beverages and Tobacco 0.11 0.03 -72% 8% <1% <1% 1.A.2.f Non-metallic Minerals 0.07 0.08 19% 3% <1% <1% 1.A.2.g Manufacturing Ind. and Constr. - other 0.78 0.36 -54% -14% 2% 1% 1.A.3 Transport 7.41 4.42 -40% -4% 18% 17% 1.A.3.a Civil Aviation 0.03 0.12 250% 9% <1% <1% 1.A.3.b Road Transportation 6.28 3.69 -41% -4% 15% 14% 1.A.3.c Railways 0.96 0.57 -41% -3% 2% 2% 1.A.3.d Navigation 0.13 0.03 -76% -27% <1% <1% 1.A.3.e Other transportation 0.00 0.00 162% -7% <1% <1% 1.A.4 Other Sectors 14.21 7.56 -47% -8% 35% 29% 1.A.4.a Commercial/Institutional 0.85 0.31 -64% -5% 2% 1% 1.A.4.b Residential 10.80 6.33 -41% -8% 26% 24% 1.A.4.c Agriculture/Forestry/Fisheries 2.56 0.92 -64% -8% 6% 3% 1.A.5 Other 0.02 0.02 10% 1% <1% <1% 1.B FUGITIVE EMISSIONS FROM FUELS 0.40 0.18 -56% -14% 1% 1%


11.16 7.86 -30% -2% 27% 30%

2.A MINERAL PRODUCTS 4.94 6.24 26% -1% 12% 24% 2.A.1 Cement Production 0.16 0.05 -66% 5% <1% <1% 2.A.2 Lime Production 0.06 0.08 43% -5% <1% <1% 2.A.3 Glass production IE IE IE IE IE IE 2.A.5 Mining, construction, handling of products 4.73 6.11 29% -1% 12% 23% 2.A.6 Other Mineral products NO NO NO NO NO NO 2.B CHEMICAL INDUSTRY 0.57 0.20 -64% -16% 1% 1% 2.C METAL PRODUCTION 4.68 0.51 -89% -2% 11% 2% 2.D NON ENERGY PRODUCTS/ SOLVENTS NE NE NE NE NE NE 2.G Other product manufacture and use 0.61 0.46 -25% -5% 1% 2% 2.H Other Processes 0.00 0.00 -26% -8% <1% <1% 2.I Wood processing 0.37 0.45 23% -1% 1% 2% 2.J Production of POPs NO NO NO NO NO NO 2.K "Consumption of POPs and heavy metals NO NO NO NO NO NO 2.L Other production, consumption, storage,… NO NO NO NO NO NO 3 AGRICULTURE 4.24 3.90 -8% <1% 10% 15% 3.B MANURE MANAGEMENT 0.56 0.50 -11% -1% 1% 2% 3.D AGRICULTURAL SOILS 3.58 3.37 -6% <1% 9% 13% 3.F FIELD BURNING OF AGRICUL. RESIDUES 0.10 0.03 -72% -1.7% <1% <1% 3.I Agriculture OTHER NO NO NO NO NO NO 5 WASTE 0.28 0.44 58% -8.4% 1% 2%




PM2.5 emissions and emission trends in Austria

National total PM2.5 emissions amounted to 27 kt in 1990 and have decreased steadily so that by the year 2018 emissions were reduced by 48% (to 14 kt) – see Table 52.

As shown in Figure 18 and Table 52, PM2.5 emissions in Austria mainly arose from combustion processes in the energy sector with a share of 84% in the total emissions in 2018. A further emis-sion source is NFR sector 2 Industrial Processes and Product Use, which had a share of 12% in national total emissions.

In general, the reduction of PM2.5 emission is due to the installation of flue gas collection and modern flue gas cleaning technologies in several branches.

Figure 20: PM2.5 emissions in Austria 1990–2018 by sectors in absolute terms.

0

5

10

15

20

25

30

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

PM2.

5 em

issi

ons

[kt]

PM2.5 emissions in Austria 1990 ‒ 2018 by NFR sectors

5 WASTE

3 AGRICULTURE



1.A.5 Other

1.A.4 Other Sectors

1.A.3 Transport






Table 52: PM2.5 emissions per NFR Category 1990 and 2018, trend 1990–2018 and share in total emissions.

NFR Category PM2.5 Emission in [kt]


1990 2018 1990– 2018

2017– 2018

1990 2018

1 ENERGY 22.76 11.99 -47% -7% 84% 84% 1.A FUEL COMBUSTION ACTIVITIES 22.65 11.93 -47% -7% 83% 84% 1.A.1 Energy Industries 0.85 0.95 11% -4% 3% 7% 1.A.2 Manufacturing Industries and Construction 1.90 0.78 -59% -10% 7% 5% 1.A.2.a Iron and Steel 0.04 0.01 -78% -7% <1% <1% 1.A.2.b Non-ferrous Metals 0.01 0.01 -21% 2% <1% <1% 1.A.2.c Chemicals 0.17 0.17 -1% -18% 1% 1% 1.A.2.d Pulp, Paper and Print 0.78 0.17 -78% 2% 3% 1% 1.A.2.e Food Processing, Beverages and Tobacco 0.09 0.03 -72% 8% <1% <1% 1.A.2.f Non-metallic Minerals 0.06 0.07 19% 3% <1% <1% 1 A 2 g Manufacturing Industries and Constr. – other 0.74 0.33 -56% -14% 3% 2% 1.A.3 Transport 6.48 3.01 -53% -6% 24% 21% 1.A.3.a Civil Aviation 0.03 0.12 250% 9% <1% 1% 1.A.3.b Road Transportation 5.71 2.65 -54% -7% 21% 19% 1.A.3.c Railways 0.60 0.21 -65% -7% 2% 1% 1.A.3.d Navigation 0.13 0.03 -76% -27% <1% <1% 1.A.3.e Other transportation 0.00 0.00 162% -7% <1% <1% 1.A.4 Other Sectors 13.41 7.17 -47% -8% 49% 50% 1.A.4.a Commercial/Institutional 0.78 0.29 -62% -5% 3% 2% 1.A.4.b Residential 10.10 5.99 -41% -8% 37% 42% 1.A.4.c Agriculture/Forestry/Fisheries 2.52 0.88 -65% -8% 9% 6% 1.A.5 Other 0.02 0.02 10% 1% <1% <1% 1.B FUGITIVE EMISSIONS FROM FUELS 0.11 0.06 -49% -14% <1% <1%


3.82 1.72 -55% -3% 14% 12%

2.A MINERAL PRODUCTS 0.71 0.79 11% -2% 3% 6% 2.A.1 Cement Production 0.14 0.05 -66% 5% 1% <1% 2.A.2 Lime Production 0.04 0.06 43% -5% <1% <1% 2.A.3 Glass production IE IE IE IE IE IE 2.A.5 Mining, construction, handling of products 0.53 0.68 29% -2% 2% 5% 2.A.6 Other Mineral products NO NO NO NO NO NO 2.B CHEMICAL INDUSTRY 0.30 0.11 -64% -16% 1% 1% 2.C METAL PRODUCTION 2.13 0.23 -89% -2% 8% 2% 2.D NON ENERGY PRODUCTS/ SOLVENTS NE NE NE NE NE NE 2.G Other product manufacture and use 0.54 0.41 -24% -5% 2% 3% 2.H Other Processes 0.00 0.00 -46% -8% <1% <1% 2.I Wood processing 0.15 0.18 23% -1% 1% 1% 2.J Production of POPs NO NO NO NO NO NO 2.K "Consumption of POPs and heavy metals NO NO NO NO NO NO 2.L Other production, consumption, storage, … NO NO NO NO NO NO 3 AGRICULTURE 0.36 0.27 -24% -1% 1% 2% 3.B MANURE MANAGEMENT 0.13 0.11 -11% -1% <1% 1% 3.D AGRICULTURAL SOILS 0.14 0.14 -3% <1% 1% 1% 3.F FIELD BURNING OF AGRICULT. RES. 0.09 0.03 -72% -2% <1% <1% 3.I Agriculture OTHER NO NO NO NO NO NO 5 WASTE 0.23 0.28 21% -13% 1% 2%




Total suspended particulate matter (TSP) emissions and emission trends in Austria

National total TSP emissions amounted to 53 kt in 1990, decreased over the period 1990 to 2018 by 28% and amounted to 38 kt in 2018, as can be seen in Table 53. TSP emissions in Austria mainly derive from 1.A Fuel Combustion Activities and 2 Industrial Processes and Prod-uct Use with shares of 44% and 41%, respectively, in national total emissions in 2018. Im-portant subcategories of 1.A Fuel Combustion Activities are 1.A.4 Other Sectors (mainly small heating installations) with a share of 21%, 1.A.3 Transport contributing with 18% as well as 1.A.1 Energy Industries with 3.2% and 1.A.2 Manufacturing Industries and Construction with 2.6% in national total emissions. NFR sector 3 Agriculture also participates with 12%.

Figure 21: TSP emissions in Austria 1990–2018 by sectors in absolute terms.

0

10

20

30

40

50

60

1990

1991

1992

1993

1994

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1997

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2011

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2014

2015

2016

2017

2018

TSP

emis

sion

s [k

t]

TSP emissions in Austria 1990 ‒ 2018 by NFR sectors

5 WASTE

3 AGRICULTURE



1.A.5 Other

1.A.4 Other Sectors

1.A.3 Transport






Table 53: TSP emissions per NFR Category 1990 and 2018, trend 1990–2018 and share in total emissions.

NFR Category TSP Emission in [kt]


1990 2018 1990– 2018

2017– 2018

1990 2018

1 ENERGY 28.60 17.43 -39% -6% 54% 45% 1.A FUEL COMBUSTION ACTIVITIES 27.74 17.05 -39% -5% 52% 44% 1.A.1 Energy Industries 1.06 1.23 17% -4% 2% 3% 1.A.2 Manufacturing Industries and Construction 2.37 1.00 -58% -9% 4% 3% 1.A.2.a Iron and Steel 0.06 0.01 -78% -7% <1% <1% 1.A.2.b Non-ferrous Metals 0.01 0.01 -21% 2% <1% <1% 1.A.2.c Chemicals 0.23 0.23 -1% -18% <1% 1% 1.A.2.d Pulp, Paper and Print 1.06 0.24 -78% 2% 2% 1% 1.A.2.e Food Processing, Beverages and Tobacco 0.12 0.03 -72% 8% <1% <1% 1.A.2.f Non-metallic Minerals 0.08 0.09 19% 3% <1% <1% 1 A 2 g Manufacturing Industries and Constr. – other 0.81 0.39 -52% -14% 2% 1% 1.A.3 Transport 9.15 6.74 -26% -2% 17% 18% 1.A.3.a Civil Aviation 0.03 0.12 250% 9% <1% <1% 1.A.3.b Road Transportation 6.98 4.98 -29% -2% 13% 13% 1.A.3.c Railways 2.00 1.61 -19% -1% 4% 4% 1.A.3.d Navigation 0.13 0.03 -76% -27% <1% <1% 1.A.3.e Other transportation 0.00 0.01 162% -7% <1% <1% 1.A.4 Other Sectors 15.16 8.06 -47% -8% 28% 21% 1.A.4.a Commercial/Institutional 0.93 0.33 -65% -5% 2% 1% 1.A.4.b Residential 11.63 6.77 -42% -8% 22% 18% 1.A.4.c Agriculture/Forestry/Fisheries 2.61 0.97 -63% -8% 5% 3% 1.A.5 Other 0.02 0.02 10% 1% <1% <1% 1.B FUGITIVE EMISSIONS FROM FUELS 0.85 0.37 -56% -14% 2% 1%


19.31 15.66 -19% -2% 36% 41%

2.A MINERAL PRODUCTS 10.21 13.00 27% -1% 19% 34% 2.A.1 Cement Production 0.17 0.06 -66% 5% <1% <1% 2.A.2 Lime Production 0.06 0.09 43% -5% <1% <1% 2.A.3 Glass production IE IE IE IE IE IE 2.A.5 Mining, construction, handling of products 9.97 12.85 29% -1% 19% 34% 2.A.6 Other Mineral products NO NO NO NO NO NO 2.B CHEMICAL INDUSTRY 0.96 0.35 -64% -16% 2% 1% 2.C METAL PRODUCTION 6.60 0.71 -89% -2% 12% 2% 2.D NON ENERGY PRODUCTS/ SOLVENTS NE NE NE NE NE NE 2.G Other product manufacture and use 0.63 0.47 -25% -5% 1% 1% 2.H Other Processes 0.00 0.00 -22% -8% <1% <1% 2.I Wood processing 0.92 1.13 23% -1% 2% 3% 2.J Production of POPs NO NO NO NO NO NO 2.K "Consumption of POPs and heavy metals NO NO NO NO NO NO 2.L Other production, consumption, storage, … NO NO NO NO NO NO 3 AGRICULTURE 4.95 4.54 -8% <1% 9% 12% 3.B MANURE MANAGEMENT 1.25 1.11 -11% -1% 2% 3% 3.D AGRICULTURAL SOILS 3.59 3.40 -5% <1% 7% 9% 3.F FIELD BURNING OF AGRICULTURAL RES. 0.10 0.03 -72% -2% <1% <1% 3.I Agriculture OTHER NO NO NO NO NO NO 5 WASTE 0.35 0.69 98% -5% 1% 2%




2.3 Emission Trends for Heavy Metals

In general emissions of heavy metals decreased remarkably from 1990 to 2018. Emission trends for heavy metals from 1990 to 2018 are presented in Table 54. Emissions for all three priority heavy metals (Cd, Pb, Hg) are well below their 1985 level, which is the obligation for Austria as a Party to the Heavy Metals Protocol. From submission 2015 onwards Austria reported all man-datory pollutants in the NFR19 reporting format from 1990 to the latest inventory year.

Table 54: National total emissions and emission trends for heavy metals 1990–2018.

Year Emissions [t]

Cd Hg Pb

1990 1.75 2.17 232.41

1991 1.66 2.06 196.32

1992 1.38 1.66 139.82

1993 1.25 1.41 99.07

1994 1.14 1.20 68.62

1995 1.05 1.22 20.36

1996 1.05 1.18 19.92

1997 1.01 1.15 18.84

1998 0.95 0.97 17.67

1999 1.01 0.95 17.92

2000 0.99 0.91 17.17

2001 1.00 0.97 16.76

2002 0.98 0.94 17.61

2003 1.00 0.98 17.80

2004 1.00 0.95 17.78

2005 1.03 0.99 18.38

2006 1.08 1.02 19.19

2007 1.11 1.03 19.94

2008 1.12 1.04 19.97

2009 1.06 0.93 17.58

2010 1.19 1.03 20.12

2011 1.16 1.02 20.40

2012 1.18 1.04 20.33

2013 1.20 1.09 21.11

2014 1.14 1.04 20.17

2015 1.15 1.01 19.57

2016 1.14 0.95 19.93

2017 1.18 1.03 20.54

2018 1.13 0.96 19.26

Trend 1990–2018 -35% -56% -92%



2.3.1 Cadmium (Cd) Emissions

Cadmium (Cd) has been ubiquitously distributed in the natural environment for millions of years. It occurs in the earth’s crust with a content estimated to be between 0.08 and 0.5 ppm. Unlike some other heavy metals, such as lead or mercury, which have been used since ancient times, Cd has been refined and utilized only since 100 years, but it was already discovered in 1817. The production and consumption of Cd has risen distinctly only since the 1940’s. The primary uses are electroplated cadmium coatings, nickel-cadmium storage batteries, pigments, and stabilizers for plastics. Publicity about the toxicity of cadmium has affected the consumption significantly.

For human beings Cd does not have a biological function unlike many other elements. The smoking (of tobacco) stands for an important exposure to Cd: smokers generally have about twice as high cadmium concentrations in the renal cortex compared to non-smokers. For the non-smoking population food is an important source of exposure because Cd is accumulated in the human and animal bodies due to its long half-life. Cd compounds and complexes are classified as an unambiguous carcinogenic working material.


The most important source for Cd emissions is the combustion of solid fuels (fossil and biomass), 1.A. Fuel Combustion Activities, contributing with a share of 74% to national total Cd emissions in 2018. The second important source is 2 Industrial Processes and Product Use with 25% in na-tional total (see Figure 22 and Table 55).

Cd emissions resulting from NFR sectors 3 Agriculture and 5 Waste are minor sources. These sectors contribute to national total Cd emissions with about 0.2% (Waste) and 0.1% (Agricul-ture).

Note: Cd emissions from NFR sector 1.B Fugitive Emissions from fuels are reported as NA.

Figure 22: Share of NFR sectors 2018 in Cd emissions.

National total Cd emissions amounted to 1.75 t in 1990; emissions have decreased and by the year 2018 emissions were reduced by 35% to 1.13 t in the period 1990–2018. However, the most significant reduction of national total Cd emissions could be achieved in the period 1985–1990. For further information see Austria´s Informative Inventory Report 2014 (UMWELTBUNDES-AMT 2014c).

74,4%

25,3%

0,1% 0,2%

Share of NFR sectors 2018 – Cd emissions




3 AGRICULTURE

5 WASTE




Between 1990 and 1998 emissions were still decreasing, mainly due a decrease in the use of heavy fuel oil and lower process emissions from iron and steel production. From 2000 to 2010 Cd emissions were increasing again, which was due to the growing activities in the industrial pro-cesses sector and energy sector. The emissions peak in 2013 can be explained with the colder winter 2013 and the resulting higher heating demand. Since then emissions remained quite stable. The increase 2017 was due to higher emissions from iron and steel production and from industrial processes.

1.A Fuel Combustion Activities In the period from 1990 to 2018 Cd emissions of 1.A Fuel Combustion Activities decreased by 20% to 0.84 t. The main sources of Cd emission within NFR sector 1.A. Fuel Combustion Activi-ties are 1.A.1 Energy Industries, 1.A.4 Other Sectors, 1.A.2 Manufacturing Industries and Con-struction. NFR 1.A.1 Energy Industries: The increasing Cd emissions since 2001 were due to increasing

use of wood and wooden litter in small combustion plants, the combustion of heavy fuel oil and residues from the petroleum processing in the refinery as well as the thermal utilisation of industrial residues and residential waste.

NFR 1.A.4 Other Sectors: Cd emissions decreased by 28% since 1990 to 0.29 t, representing a share of 26% in national total emissions in 2018. The reduction is mainly due to a decreased use of coal.

NFR 1.A.2 Manufacturing Industries and Construction: Between 1990 and 2018 Cd emis-sions decreased by 20%, however since 2000 emissions show an increasing trend due to in-creased use of biomass in pulp and paper industries.

NFR 1.A.3 Transport: The increase of Cd emission is due to the enormous increasing activity of the transport sector in passenger and freight transport. Cd emissions arise for the most part from tyre and brake abrasion. Emissions from tyre and brake wear are increasing as a function of travelled vehicles kilometres which have shown an increasing trend since 1990.

In all mentioned subcategories, except for NFR sector 1.A.3, Cd emissions have decreased since 1990, mainly due to an increase in efficiency, the implementation and installation of flue gas treatment system as well as due to dust removal systems.

2 Industrial Processes and Product Use Within sector 2 Industrial Processes and Product Use the main source for Cd emission is sub-category 2.C Metal Production. NFR 2.C Metal Production: As shown in Table 55 in the period from 1990 to 2018 the Cd

emissions decreased by 60% to 0.21 t, which is a share of 19% to the total Cd emission. Emissions from NFR 2.C.1 Iron and steel decreased significantly due to extensive abatement measures but also by production and product substitution. Compared to the previous year emissions from NFR 2.C.1 Iron and steel decreased in 2018 by 16%.



Figure 23: Cd emissions in Austria 1990–2018 by sectors in absolute terms.

0,0

0,2

0,4

0,6

0,8

1,0

1,2

1,4

1,6

1,8

2,019

9019

9119

9219

9319

9419

9519

9619

9719

9819

9920

0020

0120

0220

0320

0420

0520

0620

0720

0820

0920

1020

1120

1220

1320

1420

1520

1620

1720

18

Cd

emis

sion

s [t]

Cd emissions in Austria 1990 – 2018 by NFR sectors

5 WASTE

3 AGRICULTURE



1.A.5 Other

1.A.4 Other Sectors

1.A.3 Transport






Table 55: Cd emissions per NFR Category 1990 and 2018, trend 1990–2018 and share in total emissions.

NFR Category Cd Emission in [t] Trend Share in National Total

1990 2018 1990–2018

2017–2018

1990 2018

1 ENERGY 1.05 0.84 -20% <1% 60% 74%

1.A FUEL COMBUSTION ACTIVITIES 1.05 0.84 -20% <1% 60% 74%





1.A.2 Manufacturing Industries and Construction 0.31 0.25 -20% 15% 18% 22%

1.A.2.a Iron and Steel 0.01 0.00 -46% 5% <1% <1%

1.A.2.b Non-ferrous Metals 0.00 0.00 -1% -7% <1% <1%

1.A.2.c Chemicals 0.03 0.01 -54% -7% 2% 1%

1.A.2.d Pulp, Paper and Print 0.15 0.14 -4% 35% 9% 13%

1.A.2.e Food Processing, Beverages and Tobacco 0.00 0.00 -58% 31% <1% <1%

1.A.2.f Non-metallic Minerals 0.10 0.02 -77% -2% 6% 2%

1.A 2.g Manufacturing Industries and Constr. - other 0.02 0.06 181% -5% 1% 5%

1.A.3 Transport 0.02 0.03 76% 3% 1% 3%


1.A.3.b Road Transportation 0.02 0.03 80% 3% 1% 3%

1.A.3.c Railways 0.00 0.00 -88% -13% <1% <1%

1.A.3.d Navigation 0.00 0.00 -16% -23% <1% <1%


1.A.4 Other Sectors 0.40 0.29 -28% -9% 23% 26%


1.A.4.b Residential 0.31 0.22 -29% -9% 18% 20%

1.A.4.c Agriculture/Forestry/Fisheries 0.03 0.05 52% -9% 2% 4%

1.A.5 Other 0.00 0.00 45% 1% <1% <1%

1.B FUGITIVE EMISSIONS FROM FUELS NA NA NA NA NA NA


0.63 0.29 -55% -13% 36% 25%



2.C METAL PRODUCTION 0.54 0.21 -60% -16% 31% 19% 2.D NON ENERGY PRODUCTS/ SOLVENTS 0.00 0.00 <1% <1% <1% <1% 2.G Other product manufacture and use 0.09 0.07 -23% -4% 5% 6% 2.H Other Processes NA NA NA NA NA NA 2.I Wood processing NA NA NA NA NA NA 2.J Production of POPs NO NO NO NO NO NO 2.K "Consumption of POPs and heavy metals NO NO NO NO NO NO


3 AGRICULTURE 0.01 0.00 -81% -2% <1% <1%

5 WASTE 0.06 0.00 -97% -13% 3% <1%




2.3.2 Mercury (Hg) Emissions

Mercury (Hg) has been ubiquitously distributed in the natural environment for millions of years. It occurs in the earth’s crust with a content estimated to be about 4·10-5%. Because of its special properties, mercury has had a number of uses for a long time: the conventional application is the thermometer, barometer, and hydrometer; other important areas of use are the lighting industry and for electrical components. Mercury forms alloys with a large number of metals, these alloys also have a wide range of applications.


As can be seen in Figure 24 and Table 55 the two most important Hg emission sources are NFR sectors 1.A Fuel Combustion Activities and 2 Industrial Processes and Product Use with shares in national totals in 2018 of 64% and 31%, respectively.

NFR sectors 3 Agriculture, 1.B Fugitive Emissions from fuels and 5 Waste are only minor Hg sources. These sectors contribute to national total Hg emissions with 0.03% (Agriculture), 0.01% (1.B) and 4.1% (Waste), respectively.

Figure 24: Share of NFR sectors 2018 in Hg emissions.

In 1990 national total Hg emissions amounted to 2.2 t; since then emissions have decreased. In the year 2018 national total Hg emissions were 56% below the level of 1990 (see Table 54). Be-tween 2017 and 2018 emissions decreased by 7.0% mainly because of reduced emissions from NFR 2.C.1 Iron and Steel Production.

The overall reduction of about 56% for the period 1990 to 2018 was due to decreasing emissions from cement industries and the industrial processes sector as well as due to reduced use of coal for residential heating. Several bans in different industrial sub-sectors and in the agriculture sector led to the sharp fall of total Hg emission in Austria by the year 2000.

The main sources of Hg emissions are described in the following.

64,4%

0,01%

31,5%

0,03% 4,1%

Share of NFR sectors 2018 – Hg emissions




3 AGRICULTURE

5 WASTE





NFR 1.A Fuel Combustion (mainly 1.A.1 Energy Industries, 1.A.2 Manufacturing Industries and Construction, 1.A.4 Other Sectors): Hg emissions are a result of combustion of coal, heavy fuel oil and waste in manufacturing industries and construction, the combustion of wood, wood waste and coal in residential plants and combustion of coal and heavy fuel oil in public electricity and heat production. Overall Hg emissions could be reduced significantly by different abatement techniques such as filter installation and wet flue gas treatment in industry and due to decreasing coal consumption in the residential sector.


NFR 2.C Metal Production: Emissions from iron and steel production are the main source within this source category and increased by about 14% since 1990 due to increased activi-ties, which were partly compensated by implemented extensive abatement measures.

NFR 2.B Chemical Industry: Hg emissions from this source were remarkable in 1990 but de-creased steadily to a share of less than 0.01% in 2018. It covers processes in inorganic chemical industries reported under NFR 2.B.10 Other. The decrease is a result of abatement measures but also due to production process substitution and product substitution. Further-more, in 1999, the process of chlorine production was changed from mercury cell to mem-brane cell.

Figure 25: Hg emissions in Austria 1990–2018 by sectors in absolute terms.

0,0

0,5

1,0

1,5

2,0

2,5

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

Hg

emis

sion

s [t]

Hg emissions in Austria 1990 – 2018 by NFR sectors

5 WASTE

3 AGRICULTURE



1.A.5 Other

1.A.4 Other Sectors

1.A.3 Transport






Table 56: Hg emissions per NFR Category 1990 and 2018, trend 1990–2018 and share in total emissions.

NFR Category Hg Emission in [t] Trend Share in National Total

1990 2018 1990–2018

2017–2018

1990 2018

1 ENERGY 1.57 0.62 -61% -2% 73% 64%




1.A.1.b Petroleum refining 0.01 0.02 143% 7% <1% 2%



1.A.2.a Iron and Steel 0.00 0.00 -38% -2% <1% <1%


1.A.2.c Chemicals 0.01 0.01 -22% -18% 1% 1%

1.A.2.d Pulp, Paper and Print 0.07 0.08 23% 12% 3% 9%

1.A.2.e Food Processing, Beverages and Tobacco 0.00 0.00 -32% 9% <1% <1%


1.A.2.g Manufacturing Industries and Constr. - other 0.01 0.03 221% -6% <1% 3%

1.A.3 Transport 0.00 0.00 38% -2% <1% <1%


1.A.3.b Road Transportation 0.00 0.00 77% 1% <1% <1%

1.A.3.c Railways 0.00 0.00 -92% -8% <1% <1%

1.A.3.d Navigation 0.00 0.00 -16% -23% <1% <1%


1.A.4 Other Sectors 0.43 0.16 -62% -9% 20% 17%


1.A.4.b Residential 0.39 0.14 -63% -9% 18% 15%


1.A.5 Other 0.00 0.00 45% 1% <1% <1%

1.B FUGITIVE EMISSIONS FROM FUELS NA 0.00 NA 164% NA <1%


0.53 0.30 -43% -16% 25% 31%


2.B CHEMICAL INDUSTRY 0.27 0.00 -100% -16% 12% <1%

2.C METAL PRODUCTION 0.26 0.30 14% -16% 12% 31% 2.D NON ENERGY PRODUCTS/ SOLVENTS NA NA NA NA NA NA 2.G Other product manufacture and use 0.00 0.00 -32% -10% <1% <1% 2.H Other Processes NA NA NA NA NA NA 2.I Wood processing NA NA NA NA NA NA 2.J Production of POPs NO NO NO NO NO NO 2.K "Consumption of POPs and heavy metals NO NO NO NO NO NO


3 AGRICULTURE 0.00 0.00 -80% -2% <1% <1%

5 WASTE 0.05 0.04 -28% 3% 3% 4%




2.3.3 Lead (Pb) Emissions

In the past, automotive sources were the major contributor of lead emissions to the atmosphere. Due to Austrian regulatory efforts to reduce the content of lead in gasoline the contribution of air emissions of lead from the transportation sector has drastically declined over the past two dec-ades. Today, industrial processes, primarily metals processing, are the major sources of lead emissions. The highest air concentrations of lead are usually found in the vicinity of smelters and battery manufacturers. Exposure to lead occurs mainly through inhalation of air and inges-tion of lead in food, water, soil, or dust. It accumulates in the blood, bones, and soft tissues and can adversely affect the kidneys, liver, nervous system, and other organs. Lead can also be de-posited on the leaves of plants, which pose a hazard to grazing animals and humans through ingestion via food chain.


As it is shown in Figure 26 and Table 57, today’s Pb emissions mainly arise from the NFR 1.A Fuel Combustion Activities and 2 Industrial Processes and Product Use with shares in national total emissions of 60% and 40%, respectively.

Pb emissions resulting from NFR sectors 3 Agriculture and 5 Waste are minor sources. These sectors contribute to national total Pb emissions with about 0.01% each.

Note: Pb emissions from NFR sector 1.B Fugitive Emissions from fuels are reported as NA.

Figure 26: Share of NFR sectors 2018 in Pb emissions.

In 1990 national total Pb emissions amounted to 232 t; emissions have decreased sharply until 1995 mainly due to enforced laws, while since the mid 90ies emissions remained quite stable. In the year 2018 emissions were 92% lower than in 1990 and amounted to 19 t. Compared to the previous year Pb emissions show a decrease of 6.2% as a result of reduced emissions from Iron and Steel Production (2.C.1).

59,6%

40,4%

0,01% 0,01%

Share of NFR sectors 2018 – Pb emissions




3 AGRICULTURE

5 WASTE




1.A Fuel Combustion Activities NFR 1.A.2 Manufacturing Industries and Construction and NFR 1.A.4 Other Sectors: Pb

emissions have decreased steadily mainly due to an increase in efficiency, implementation and installation of flue gas treatment system as well as due to dust removal systems.

NFR 1.A.1 Energy Industries: Increasing Pb emissions could be noted in the last decade due to increasing activities.

NFR 1.A.4 Other Sectors: Between 1990 and 2018 emissions decreased steadily due to a decreased use of coal and a reduced content of Pb in the heating oil.

NFR 1.A.3 Transport: By the conditions laid down in European directives, emission limits for cars and trucks as well as more stringent quality requirements for fuels lead to almost com-pletely reduced Pb emissions from the transport sector. From 1990 to 1995 lead emissions from this sub-sector decreased by 98%.

2 Industrial Processes and Product Use NFR 2.C Metal Production: Emissions from this sub sector decreased significantly between

1990 and 2018 (-81%) due to extensive abatement measures but also due to production pro-cess substitution and product substitution.

In addition to emission reduction in the energy sector the sector industrial processes reduced its emissions remarkably due to improved dust abatement technologies.

Figure 27: Pb emissions in Austria 1990–2018 by sectors in absolute terms.

0

50

100

150

200

250

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

Pb e

mis

sion

s [t]

Pb emissions in Austria 1990 – 2018 by NFR sectors

5 WASTE

3 AGRICULTURE



1.A.5 Other

1.A.4 Other Sectors

1.A.3 Transport






Table 57: Pb emissions per NFR Category 1990 and 2018, trend 1990–2018 and share in total emissions.

NFR Category Pb Emission in [t] Trend Share in National Total

1990 2018 1990–2018

2017–2018

1990 2018

1 ENERGY 193.98 11.47 -94% <1% 83% 60%

1.A FUEL COMBUSTION ACTIVITIES 193.98 11.47 -94% <1% 83% 60%

1.A.1 Energy Industries 1.47 2.38 62% -2% 1% 12%

1.A.1.a Public Electricity and Heat Production 1.27 1.91 50% -4% 1% 10%

1.A.1.b Petroleum refining 0.19 0.47 143% 7% <1% 2%



1.A.2.a Iron and Steel 0.26 0.15 -42% 5% <1% 1%

1.A.2.b Non-ferrous Metals 0.00 0.00 20% -10% <1% <1%

1.A.2.c Chemicals 0.21 0.27 29% -9% <1% 1%

1.A.2.d Pulp, Paper and Print 0.65 0.98 51% 15% <1% 5%

1.A.2.e Food Processing, Beverages and Tobacco 0.01 0.01 66% 30% <1% <1%



1.A.3 Transport 179.54 4.81 -97% 4% 77% 25%

1.A.3.a Civil Aviation 1.64 0.00 -100% <1% 1% <1%

1.A.3.b Road Transportation 177.64 4.81 -97% 4% 76% 25%

1.A.3.c Railways 0.01 0.00 -93% -6% <1% <1%

1.A.3.d Navigation 0.25 0.00 -100% -17% <1% <1%


1.A.4 Other Sectors 7.38 2.04 -72% -9% 3% 11%

1.A.4.a Commercial/Institutional 0.36 0.14 -62% -12% <1% 1%

1.A.4.b Residential 6.01 1.75 -71% -9% 3% 9%

1.A.4.c Agriculture/Forestry/Fisheries 1.01 0.16 -85% -9% <1% 1%

1.A.5 Other 0.00 0.00 45% 1% <1% <1%



37.41 7.78 -79% -14% 16% 40%



2.C METAL PRODUCTION 36.17 6.93 -81% -15% 16% 36% 2.D NON ENERGY PRODUCTS/ SOLVENTS 0.02 0.02 <1% <1% <1% <1% 2.G Other product manufacture and use 1.22 0.83 -32% -10% 1% 4% 2.H Other Processes NA NA NA NA NA NA 2.I Wood processing NA NA NA NA NA NA 2.J Production of POPs NO NO NO NO NO NO 2.K "Consumption of POPs and heavy metals NO NO NO NO NO NO


3 AGRICULTURE 0.00 0.00 -34% <1% <1% <1%

5 WASTE 1.02 0.00 -100% -6% <1% <1%




2.4 Emission Trends for POPs

In submission 2020 Austria reports for the first time all mandatory pollutants in the NFR19 re-porting format from 1990 to the latest inventory year. Emissions of the years before 1990 were last updated and published in submission 201471. PCB emissions are reported from submission 2016 onwards.

Emissions of all POPs decreased remarkably from 1990 to 2018 (HCB -58%, PAH -64%, PCDD/F -73% and PCBs -32%), where the highest achievement was made until 1995. The sig-nificant increase of HCB emissions in the years 2012, 2013 and 2014 was due to unintentional releases of HCB by an Austrian cement plant.

In 2018 PCB emissions decreased by 16% compared to the previous year 2017, due to reduced emissions from sector 2.C.1 Iron and Steel Production. PCDD/F emissions decreased by 7.5% compared to the previous year 2017, PAH emissions decreased by 8.1% and HCB emissions by 9.6% in the same time. These reductions are mainly due to the warm weather and thus reduced emissions from residential heating (decreased bio-mass consumption) as well as due to a decrease of iron and steel production (2.C.1) (relevant for HCB and PCDD/F). Dioxin/furan emissions from sector Waste (5.E Other Waste) also de-creased remarkably from 2017 to 2018.

The most important source for PAH, PCDD/F and HCB emissions in Austria is residential heat-ing. In the 80s industry and waste incineration were still important sources regarding POP emis-sions. Due to legal regulations concerning air quality emissions from industry and waste incin-eration decreased remarkably from 1990 to 1993.

For PCB emissions the most important source category is 2.C Metal Production.

PAH emissions from NFR subcategory 2.D.3 Solvent Use stopped in 1997, emissions of diox-in/furan (PCDD/F) stopped in 1993 and emissions of HCB stopped in 2001.

Table 58: Emissions and emission trends for POPs 1990–2018.

Year Emission

PAH [t] PCDD/F [g] HCB [kg] PCB [kg]

1990 19.03 125.17 85.50 47.23

1991 19.77 124.81 86.39 35.89

1992 14.59 76.55 76.24 28.87

1993 11.75 66.63 71.19 29.16

1994 10.55 56.35 58.03 26.91

1995 10.79 57.66 58.34 29.16

1996 11.29 57.89 58.94 26.37

1997 10.14 58.17 55.99 29.95

1998 9.48 54.95 51.72 30.20

1999 9.25 51.63 49.47 28.76

2000 8.54 50.41 43.33 30.18

2001 8.68 50.68 44.17 30.64

2002 7.82 37.66 40.55 31.46

71 Austria´s submission 2014 under the Convention on Long-range Transboundary Air Pollution covering the years

1980‒2012: http://www.ceip.at/ms/ceip_home1/ceip_home/status_reporting/2014_submissions/




Year Emission

PAH [t] PCDD/F [g] HCB [kg] PCB [kg]

2003 7.45 36.91 39.24 31.71

2004 7.23 36.12 37.72 32.54

2005 7.24 35.77 37.74 34.93

2006 7.47 37.10 38.35 35.24

2007 7.45 36.85 37.73 36.48

2008 7.44 36.47 38.07 36.40

2009 7.33 36.32 37.41 27.54

2010 8.07 41.00 42.87 34.55

2011 7.42 38.18 39.41 35.30

2012 7.69 39.04 64.49 34.83

2013 7.87 39.74 143.67 37.16

2014 7.02 36.66 144.49 36.64

2015 7.29 37.70 37.27 35.69

2016 7.35 37.25 38.09 34.72

2017 7.39 37.18 39.40 38.22

2018 6.80 34.41 35.63 32.09

Trend 1990–2018 -64% -73% -58% -32%



2.4.1 Polycyclic Aromatic Hydrocarbons (PAH) Emissions

The polycyclic aromatic hydrocarbons (PAH) are molecules built up of benzene rings which re-semble fragments of single layers of graphite. PAHs are a group of approximately 100 com-pounds. Most PAHs in the environment arise from incomplete burning of carbon-containing mate-rials like oil, wood, garbage or coal. Fires are able to produce fine PAH particles, they bind to ash particles and sometimes move long distances through the air. Thus PAHs have been ubiqui-tously distributed in the natural environment since thousands of years.

Out of all different compounds of the pollutant group of PAHs, the four compounds benz(a)pyren, benzo(b)fluoranthen, benzo(k)fluoranthen and indeno(1,2,3-cd)pyren are used as indicators for the purposes of emission inventories, which has been specified in the UNECE POPs Protocol mentioned above.


In 1990 the main emission sources for PAH emissions were NFR 1.A Fuel Combustion Activi-ties (62%) and Industrial Processes and Product Use (38%). In 2018 emissions are almost ex-clusively emitted by source category 1.A Fuel Combustion Activities with 96% of national total PAH emissions as it is illustrated in Figure 28 and Table 59. NFR sector Industrial Processes and Product Use contributes in 2018 with 3.1% of national total emissions. From 1990 to 2018 PAH emissions from Agriculture decreased remarkably by 49% due to pro-hibition of open field burning. In 2018 NFR sectors 3 Agriculture (0.6%) and 5 Waste (<0.1%) are minor sources.

Note: PAH emissions from NFR sector 1.B Fugitive Emissions from fuels are reported as NA.

Figure 28: Share of NFR sectors 2018 in PAH emissions.

In 1990 national total PAH emissions amounted to 19.0 t; emissions have decreased since then, where the main achievement was made until 1993, by the year 2018 emissions were reduced by about 64% (to 6.8 t in 2018).

96,2%

3,1% 0,6% 0,0003%

Share of NFR sectors 2018 – PAH emissions




3 AGRICULTURE

5 WASTE





In 2018 PAH emissions are largely emitted by 1.A Fuel Combustion Activities with a share of 96% in national total emissions. Within this source, PAH emissions mainly result from sector 1.A.4.b Residential (stationary), and to a much smaller extent from NFR sectors 1.A.4.c Agricul-ture/Forestry/Fisheries (stationary) and 1.A.3 Transport. 1.A.4.b Residential (stationary): Emissions have decreased since 1990 by 54% because of a

decreased use of coal and an increased share of efficient biomass boilers with lower specific emissions. Compared to the previous year 2017 emissions decreased by 8.8% due to the warm weather.

1.A.4.c Agriculture/Forestry/Fisheries (stationary): Compared to 1990 emissions have in-creased by 81% as a result of a higher biomass consumption. Between 2017 and 2018 emis-sions decreased by 8.3%, that was also due to the warm weather.

1.A.3 Transport: Emissions have increased by 17% since 1990 due to increased activities (emissions here result from exhaust and non-exhaust (tyre- and brake-wear) activities). A re-duction potential results in the future by reducing the soot emissions of diesel-powered vehi-cles because the PAHs are mostly attached to the microparticles.


PAH emissions from the sector Industrial processes and Product Use decreased by 97% since 1990 due to the shutdown of primary aluminium production in Austria, which was a main source for PAH emissions.

Figure 29: PAH emissions in Austria 1990–2018 by sectors in absolute terms.

0

5

10

15

20

25

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

PAH

em

issi

ons

[t]

PAH emissions in Austria 1990 – 2018 by NFR sectors

5 WASTE

3 AGRICULTURE



1.A.5 Other

1.A.4 Other Sectors

1.A.3 Transport






Table 59: PAH emissions per NFR Category 1990 and 2018, trend 1990–2018 and share in total emissions.

NFR Category PAH Emission in [t]


1990 2018 1990–2018

2017– 2018

1990 2018

1 ENERGY 11.81 6.54 -45% -8% 62% 96% 1.A FUEL COMBUSTION ACTIVITIES 11.81 6.54 -45% -8% 62% 96% 1.A.1 Energy Industries 0.01 0.03 389% -4% <1% <1% 1.A.2 Manufacturing Industries and Construction 0.06 0.22 237% <1% <1% 3% 1.A.2.a Iron and Steel 0.00 0.00 -34% <1% <1% <1% 1.A.2.b Non-ferrous Metals 0.00 0.00 -24% <1% <1% <1% 1.A.2.c Chemicals 0.02 0.02 17% -13% <1% <1% 1.A.2.d Pulp, Paper and Print 0.00 0.00 25% 5% <1% <1% 1.A.2.e Food Processing, Beverages and Tobacco 0.00 0.00 -14% 15% <1% <1% 1.A.2.f Non-metallic Minerals 0.00 0.01 122% 3% <1% <1% 1.A.2.g Manufacturing Industries and Constr. - other 0.04 0.18 389% 1% <1% 3% 1.A.3 Transport 0.29 0.34 17% <1% 2% 5% 1.A.3.a Civil Aviation NE NE NE NE NE NE 1.A.3.b Road Transportation 0.26 0.33 23% 1% 1% 5% 1.A.3.c Railways 0.02 0.01 -58% -20% <1% <1% 1.A.3.d Navigation 0.01 0.00 -15% -24% <1% <1% 1.A.3.e Other transportation 0.00 0.00 162% -7% <1% <1% 1.A.4 Other Sectors 11.45 5.96 -48% -9% 60% 88% 1.A.4.a Commercial/Institutional 0.30 0.08 -73% -2% 2% 1% 1.A.4.b Residential 10.62 4.93 -54% -9% 56% 72% 1.A.4.c Agriculture/Forestry/Fisheries 0.53 0.95 81% -8% 3% 14% 1.A.5 Other 0.00 0.00 -7% <1% <1% <1% 1.B FUGITIVE EMISSIONS FROM FUELS NA NA NA NA NA NA 2 INDUSTRIAL PROCESSES AND

PRODUCT USE 7.14 0.21 -97% -14% 38% 3%

2.A MINERAL PRODUCTS IE IE IE IE IE IE 2.B CHEMICAL INDUSTRY NE NE NE NE NE NE 2.C METAL PRODUCTION 6.44 0.17 -97% -16% 34% 3% 2.C.1 Iron and Steel Production 0.35 0.17 -50% -16% 2% 3% 2.C.2 Ferroalloys Production NE NE NE NE NE NE 2.C.3 Aluminium production 6.09 NE NE NE 32% NE 2.C.4 Magnesium production NO NO NO NO NO NO 2.C.5 Lead Production NA NA NA NA NA NA 2.C.6 Zinc production NO NO NO NO NO NO 2.C.7 Other metal production NE NE NE NE NE NE 2.D NON ENERGY PRODUCTS/ SOLVENTS 0.15 NA NA NA 1% NA 2.G Other product manufacture and use 0.00 0.00 -22% -4% <1% <1% 2.H Other Processes 0.55 0.04 -93% <1% 3% 1% 2.I Wood processing NA NA NA NA NA NA 2.J Production of POPs NO NO NO NO NO NO 2.K "Consumption of POPs and heavy metals NO NO NO NO NO NO 2.L Other production, consumption, storage, … NO NO NO NO NO NO 3 AGRICULTURE 0.08 0.04 -49% -1% <1% 1% 5 WASTE 0.00 0.00 -92% 3% <1% <1% Total without sinks 19.03 6.80 -64% -8%



2.4.1.1 Benzo(a)pyrene , Benzo(b)floranthene, Benzo(k)fluoranthene, Indeno (1,2,3-cd) pyrene

In the NFR Tables of submission 2020 Austria reports Total 1-4 PAH emissions for all relevant source categories and all years. However, the estimation of emissions by PAH species is work in progress. For some source categories PAH emissions are already calculated on the level of different PAH species including a methodological description in the IIR. Austria will report emis-sions of 4 PAH species separately in its next inventory submission for all relevant source cate-gories and all years.



2.4.2 Dioxins and Furan (PCDD/F)

Dioxins form a family of toxic chlorinated organic compounds that share certain chemical struc-tures and biological characteristics. Several hundred of these compounds exist and are mem-bers of three closely related families: the chlorinated dibenzo(p)dioxins (CDDs), chlorinated dibenzofurans (CDFs) and certain polychlorinated biphenyls (PCBs). Dioxins bio-accumulate in humans and wildlife due to their fat solubility and 17 of these compounds are especially toxic.

Dioxins are formed as a result of combustion processes such as commercial or municipal waste incineration and from burning fuels like wood, coal or oil as a main source of dioxins. Dioxins can also be formed when household trash is burned and as a result of natural processes such as forest fires. Dioxins enter the environment also through the production and use of organ chlo-rinated compounds: chlorine bleaching of pulp and paper, certain types of chemical manufactur-ing and processing, and other industrial processes are able to create small quantities of dioxins. Cigarette smoke also contains small amounts of dioxins.

Due to stringent legislation and modern technology, dioxin emissions from combustion and incin-eration as well as from chemical manufacturing and processes have been reduced dramatically. Nowadays domestic combustion as well as thermal processes in metals extraction and pro-cessing have become more significant.

Main sources and emission trend in Austria

The main source for dioxin and furan emissions in Austria, with a share of 74% in 2018, is cate-gory 1.A Fuel Combustion Activities (see Figure 30 and Table 60). Sector 2 Industrial Processes and Product Use contributes with 19% in national total emissions.

In 2018 PCDD/F emissions from sectors 3 Agriculture has a share of only 0.2% in national total emissions (3.F Field burning of agricultural residues is the only source). NFR sector 5 Waste contributes with 6.9% to national total emissions (mainly due to 5.E Other Waste comprising unwanted fires in cars and various types of houses).

Note: Dioxin/furan emissions from NFR sector 1.B Fugitive Emissions from fuels are reported as NA.

Figure 30: Share of NFR sectors 2018 in Dioxin/furan emissions.

74,4%

18,6%

0,2% 6,9%

Share of NFR sectors 2018 – Dioxin/furan emissions




3 AGRICULTURE

5 WASTE




In 1990 national total dioxin/furan (PCDD/F) emissions amounted to about 125 g; emissions have decreased since then, where the main achievement was made until 1993, by the year 2018 emissions were reduced by about 73% (to 34 g in 2018).

1.A Fuel Combustion Activities In more detail within sector 1.A Fuel Combustion Activities, the main sources of dioxin and furan emissions are: NFR 1.A.4 Other Sectors: This sector has the highest contribution (55%) to national total diox-

in/furan (PCDD/F) emissions in 2018 within source 1.A Fuel Combustion Activities due to bi-omass heating.

NFR 1.A.2 Manufacturing Industries and Construction: Emissions increased significantly since 1990 and contribute with 11% to national dioxin/furan (PCDD/F) emissions in 2018.

2 Industrial Processes and Product Use The second largest source is sector 2 Industrial Processes and Product Use (19% in national total emissions in 2018). NFR 2.C Metal Production: Dioxin/furan (PCDD/F) emissions decreased remarkably due to

extensive abatement measures since 1990 (-84%). Within this sector emissions are emitted by subcategories 2.C.1 Iron and Steel Production, 2.C.3 Aluminium Production, 2.C.5 Lead Production and 2.C.7 Other metal production (copper production).

5 Waste 5 Waste: From 1990 to 2018 dioxin/furan (PCDD/F) emissions from sector Waste decreased

by 88% due to stringent legislation and modern technology. As shown in Table 60 in the peri-od from 1990 to 2018 dioxin/furan emissions decreased to 2.37 g, which is a share of 6.9% in total dioxin/furan emissions, whereas in 1990 dioxin/furan (PCDD/F) emissions contributed 16% to the total dioxin/furan emissions. Within sector Waste the main emission source is 5.E Other Waste comprising emissions from unintential fires, which is rated as a key source for dioxin/furan (PCDD/F) emissions in 2018.

Figure 31: Dioxin/Furan emissions in Austria 1990–2018 by sectors in absolute terms.

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Dioxin/furan emissions in Austria 1990 – 2018 by NFR sectors

5 WASTE

3 AGRICULTURE



1.A.5 Other

1.A.4 Other Sectors

1.A.3 Transport






Table 60: Dioxin/Furan (PCDD/F) emissions per NFR Category 1990 and 2018, trend 1990–2018 and share in total emissions.

NFR Category Dioxin Emission in [g]


1990 2018 1990–2018

2017–2018

1990 2018

1 ENERGY 61.85 25.58 -59% -7% 49% 74% 1.A FUEL COMBUSTION ACTIVITIES 61.85 25.58 -59% -7% 49% 74% 1.A.1 Energy Industries 12.14 1.34 -89% -5% 10% 4% 1.A.2 Manufacturing Industries and Construction 1.68 3.62 116% -3% 1% 11% 1.A.2.a Iron and Steel 0.03 0.03 -24% 3% <1% <1% 1.A.2.b Non-ferrous Metals 0.02 0.04 87% 1% <1% <1% 1.A.2.c Chemicals 0.44 0.52 19% -12% <1% 2% 1.A.2.d Pulp, Paper and Print 0.50 0.62 25% 5% <1% 2% 1.A.2.e Food Processing, Beverages and Tobacco 0.03 0.04 52% 14% <1% <1% 1.A.2.f Non-metallic Minerals 0.29 0.48 63% 3% <1% 1% 1.A.2.g Manufacturing Industries and Constr. - other 0.37 1.90 413% -5% <1% 6% 1.A.3 Transport 4.16 1.57 -62% <1% 3% 5% 1.A.3.a Civil Aviation NE NE NE NE NE NE 1.A.3.b Road Transportation 4.11 1.55 -62% <1% 3% 4% 1.A.3.c Railways 0.04 0.01 -71% -18% <1% <1% 1.A.3.d Navigation 0.01 0.01 -18% -14% <1% <1% 1.A.3.e Other transportation 0.00 0.00 162% -7% <1% <1% 1.A.4 Other Sectors 43.87 19.05 -57% -9% 35% 55% 1.A.4.a Commercial/Institutional 1.74 0.51 -71% -9% 1% 1% 1.A.4.b Residential 40.59 17.18 -58% -8% 32% 50% 1.A.4.c Agriculture/Forestry/Fisheries 1.53 1.36 -11% -10% 1% 4% 1.A.5 Other 0.00 0.00 28% <1% <1% <1% 1.B FUGITIVE EMISSIONS FROM FUELS NA NA NA NA NA NA 2 INDUSTRIAL PROCESSES AND

PRODUCT USE 42.85 6.40 -85% -6% 34% 19%

2.A MINERAL PRODUCTS IE IE IE IE IE IE 2.B CHEMICAL INDUSTRY NA NA NA NA NA NA 2.C METAL PRODUCTION 40.00 6.27 -84% -6% 32% 18% 2.C.1 Iron and Steel Production 37.21 2.50 -93% -13% 30% 7% 2.C.2 Ferroalloys Production NE NE NE NE NE NE 2.C.3 Aluminium production 2.40 3.30 37% <1% 2% 10% 2.C.4 Magnesium production NO NO NO NO NO NO 2.C.5 Lead Production 0.07 0.07 4% <1% <1% <1% 2.C.6 Zinc production NO NO NO NO NO NO 2.C.7 Other metal production 0.32 0.40 26% <1% <1% 1% 2.D NON ENERGY PRODUCTS/ SOLVENTS 1.06 NA NA NA 1% NA 2.G Other product manufacture and use 0.00 0.00 -22% -4% <1% <1% 2.H Other Processes 1.79 0.13 -93% <1% 1% <1% 2.I Wood processing NA NA NA NA NA NA 2.J Production of POPs NO NO NO NO NO NO 2.K "Consumption of POPs and heavy metals NO NO NO NO NO NO 2.L Other production, consumption, storage, … NO NO NO NO NO NO 3 AGRICULTURE 0.18 0.05 -70% -6% <1% <1% 5 WASTE 20.29 2.37 -88% -15% 16% 7% Total without sinks 125.17 34.41 -73% -7%



2.4.3 Hexachlorobenzene (HCB) Emissions

Hexachlorobenzene (HCB) has been widely employed as a fungicide on seeds, especially against the fungal disease ‘bunt’ that affects some cereal crops. The marketing and use of hexa-chlorobenzene as a plant protection product was banned in the European Union in 1988.

As there is no more hexachlorobenzene production in the EU, the only man-made releases of hexachlorobenzene are as unintentional by-product; it is emitted from the same chemical and thermal processes as Dioxins/Furans (PCDD/F) and formed via a similar mechanism.

It is released to the environment as an unintentional by-product in chemical industry (production of several chlorinated hydrocarbons such as drugs, pesticides or solvents) and in metal indus-tries and is formed in combustion processes in the presence of chlorine.


As can be seen in Figure 32 and Table 61 the main HCB emission source in 2018 is NFR sector 1.A Fuel Combustion Activities with 81% in national total emissions. Sector 2 Industrial Pro-cesses and Product Use has a share of 15% in national total emissions. From 1990 to 2018 HCB emissions from the sectors NFR 3 Agriculture as well as NFR 5 Waste decreased remarkably by 85% and 84%, respectively, due to stringent legislation and modern technology. Both sectors are minor sources of HCB emissions in 2018 with shares of 4.3% (Ag-riculture) and 0.2% (Waste) in national total emissions.

Note: HCB emissions from NFR sector 1.B Fugitive Emissions from fuels are reported as NA.

Figure 32: Share of NFR sectors 2018 in HCB emissions.

Total emissions of HCB are decreasing over the period 1990–2018 by 58%. However, due to un-intentional HCB releases in 2012, 2013 and 2014 emissions rose to a very high level: HCB con-taminated material (lime) was co-incinerated in a cement plant at too low temperatures, that’s why the HCB was not destroyed as planned. The sharp decrease of total emissions between 2014 and 2015 by 74% can therefore be explained as emissions in 2015 were at the usual level again. Between 2017 and 2018 HCB emissions decreased by 9.6% mainly due to reduced emissions from residential heating (decreased biomass consumption).

80,5%

15,0%

4,3% 0,2%

Share of NFR sectors 2018 – HCB emissions




3 AGRICULTURE

5 WASTE




1.A Fuel Combustion Activities Within this source category the small combustion sector (i.e. residential heating) is the most im-portant sector. HCB emissions of sector 1.A decreased by 48% since 1990. 1.A.4 Other Sectors: This subcategory had a share of 63% in 1990 and 77% in 2018 and is

the highest contributor within sector 1.A Fuel Combustion Activities due to the high amounts of biomass used in the residential sector. Since 1990 emissions decreased by 49%. Com-pared to the previous year a decrease of 9.1% can be observed 2018, due to the reduced bi-omass use as a consequence of lower demand for space heating.

2 Industrial Processes and Product Use The second largest source for HCB emissions in 2018 was sector 2 Industrial Processes and Product Use (mainly Iron and Steel Production) with a share of 15% in national total emissions. HCB emissions of this sector decreased by 73% between 1990 and 2018. This reduction could be mainly achieved with abatement measures in iron and steel industry. HCB was also a by-product of chlorinated pesticides, which production was banned step-by-step in the beginning of the 1990s.

Figure 33: HCB emissions in Austria 1990–2018 by sectors in absolute terms.

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HCB emissions in Austria 1990 – 2018 by NFR sectors

5 WASTE

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1.A.5 Other

1.A.4 Other Sectors

1.A.3 Transport






Table 61: Hexachlorbenzene (HCB) emissions per NFR Category 1990 and 2018, trend 1990–2018 and share in total emissions.

NFR Category HCB Emission in [kg]


1990 2018 1990– 2018

2017– 2018

1990 2018

1 ENERGY 54.89 28.69 -48% -9% 64% 81%


1.A.1 Energy Industries 0.28 0.49 78% -4% <1% 1%

1.A.2 Manufacturing Industries and Construction 0.29 0.60 106% -3% <1% 2%

1.A.2.a Iron and Steel 0.01 0.00 -30% 4% <1% <1%

1.A.2.b Non-ferrous Metals 0.00 0.00 -48% 6% <1% <1%

1.A.2.c Chemicals 0.07 0.08 19% -10% <1% <1%

1.A.2.d Pulp, Paper and Print 0.10 0.12 25% 5% <1% <1%

1.A.2.e Food Processing, Beverages and Tobacco 0.00 0.01 65% 18% <1% <1%

1.A.2.f Non-metallic Minerals 0.06 0.08 44% 2% <1% <1%


1.A.3 Transport 0.83 0.31 -62% <1% 1% 1%

1.A.3.a Civil Aviation NE NE NE NE NE NE

1.A.3.b Road Transportation 0.82 0.31 -62% <1% 1% 1%

1.A.3.c Railways 0.01 0.00 -71% -18% <1% <1%

1.A.3.d Navigation 0.00 0.00 -18% -14% <1% <1%


1.A.4 Other Sectors 53.49 27.29 -49% -9% 63% 77%


1.A.4.b Residential 50.05 24.52 -51% -9% 59% 69%

1.A.4.c Agriculture/Forestry/Fisheries 1.89 2.32 23% -9% 2% 7%

1.A.5 Other 0.00 0.00 28% <1% <1% <1%



20.07 5.36 -73% -12% 23% 15%


2.B CHEMICAL INDUSTRY 1.26 NA NA NA 1% NA

2.C METAL PRODUCTION 9.40 5.33 -43% -12% 11% 15%

2.C.1 Iron and Steel Production 8.09 3.54 -56% -17% 9% 10%

2.C.2 Ferroalloys Production NE NE NE NE NE NE

2.C.3 Aluminium production 1.20 1.65 37% <1% 1% 5%

2.C.4 Magnesium production NO NO NO NO NO NO

2.C.5 Lead Production NA NA NA NA NA NA

2.C.6 Zinc production NO NO NO NO NO NO

2.C.7 Other metal production 0.10 0.14 40% <1% <1% <1%

2.D NON ENERGY PRODUCTS/ SOLVENTS 9.05 NA NA NA 11% NA

2.G Other product manufacture and use NE NE NE NE NE NE

2.H Other Processes 0.36 0.03 -93% <1% <1% <1%





3 AGRICULTURE 10.15 1.52 -85% -16% 12% 4%

5 WASTE 0.39 0.06 -84% 4% <1% <1%




2.4.4 Polychlorinated biphenyl (PCB) Emissions

Polychlorinated Biphenyls are a class of synthetic organic chemicals and there are 209 configu-rations. Since 1930 until the beginning of the 1980´s PCBs were used for a variety of industrial uses (mainly as dielectric fluids in capacitors and transformers but also as flame retardants, ink solvents, plasticizers etc.) because of their chemical stability (fire resistance, low electrical con-ductivity, high resistance to thermal breakdown and a high resistance to oxidants and other chemicals)72.

PCBs have entered the environment through both use and disposal. PCBs can be easily carried along from the place of contamination and are distributed in all global ecosystems (UMWELT-BUNDESAMT 1996). Because of its substantial characteristics PCB is persistent. As it is also lipo-soluble it is easily accumulated in the food chain (BAYERISCHES LANDESAMT FÜR UMWELT 2008).

PCB production was banned by the United States Congress in 1979 and by the Stockholm Convention on Persistent Organic Pollutants73 in 2001 because of its environmental toxicity and classification as a persistent organic pollutant. As PCB is no longer produced in the EU, the only man-made release of PCB is as unintentionally produced pollutant (UMWELTBUNDESAMT 2012).


Austrian PCB emissions are almost exclusively emitted in NFR sector 2 Industrial Processes and Product Use with a share of 95% in national total PCB emissions in 2018 (see Figure 34 and Table 62). NFR 1.A Fuel Combustion Activities, both from stationary and mobile sources (NFR 1.A.3 Transport), is a minor source of PCB emissions with a share of 5.2% in total emissions in 2018. PCB emissions from stationary combustion are decreasing since 1990, mainly due to a reduced consumption of coal and bunker oil. Emissions from subcategory Transport are a minor source and do not influence the emission trend.

Note: PCB emissions from NFR sector 1.B Fugitive Emissions from fuels are reported as NA.

Figure 34: Share of NFR sectors 2018 in PCB emissions. 72 http://chm.pops.int/Implementation/PCBs/Overview/tabid/273/Default.aspx 73 http://chm.pops.int/default.aspx

5,2%

94,7%

Share of NFR sectors 2018 – PCB emissions




3 AGRICULTURE

5 WASTE


http://chm.pops.int/Implementation/PCBs/Overview/tabid/273/Default.aspx

http://chm.pops.int/default.aspx



In 1990 national total PCB emissions amounted to about 47 kg; emissions have decreased by 32% and in 2018 emissions were at the level of 32 kg. The emission trend is largely influenced by metal production. Between 2017 and 2018 emissions decreased by 16%, due to reduced emissions from sector 2.C.1 Iron and Steel Production. 2 Industrial Processes and Product Use Within the IPPU sector, all of the PCB is arising from subcategory NFR 2.C Metal Production: NFR category 2.C.1 Iron and Steel Production is the main source of national total PCB emis-sions in 2018. Emissions from 2.C.5 Lead Production and 2.C.7 Other Metal Production are mi-nor sources in 2018. However, PCB emissions from 2.C.5 Lead Production decreased by nearly 100% since 1990. The biggest reduction could be achieved between 1990 and 1993 due to the phase out of the only primary lead production plant in Austria. Since 1990 emissions from sub-category 2.C decreased by 21%; the emissions generally follow the production activities but the decrease is also due to abatement technologies.

Figure 35: PCB emissions in Austria 1990–2018 by sectors in absolute terms.

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PCB emissions in Austria 1990 – 2018 by NFR sectors

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1.A.5 Other

1.A.4 Other Sectors

1.A.3 Transport






Table 62: Polychlorinated biphenyl (PCB) emissions per NFR Category 1990 and 2018, trend 1990–2018 and share in total emissions.

NFR Category PCB Emission in [kg]


1990 2018 1990–2018

2017–2018

1990 2018

1 ENERGY 8.73 1.67 -81% -18% 18% 5%


1.A.1 Energy Industries 1.16 0.05 -96% -72% 2% <1%


1.A.2.a Iron and Steel 0.08 0.02 -75% -7% <1% <1%


1.A.2.c Chemicals 0.21 0.24 14% -40% <1% 1%

1.A.2.d Pulp, Paper and Print 1.49 0.72 -52% -7% 3% 2%

1.A.2.e Food Processing, Beverages and Tobacco 0.15 0.02 -85% -23% <1% <1%


1.A.2.g Manufacturing Industries and Constr. - other 0.19 0.01 -92% -66% <1% <1%

1.A.3 Transport 0.00 0.00 -1% -12% <1% <1%

1.A.4 Other Sectors 4.92 0.15 -97% -11% 10% <1%


1.A.4.b Residential 4.53 0.14 -97% -11% 10% <1%

1.A.4.c Agriculture/Forestry/Fisheries 0.09 0.00 -95% -11% <1% <1%

1.A.5 Other 0.00 0.00 -69% -21% <1% <1%



38.50 30.40 -21% -16% 82% 95%


2.B CHEMICAL INDUSTRY NA NA NA NA NA NA

2.C METAL PRODUCTION 38.50 30.40 -21% -16% 82% 95%

2.C.1 Iron and Steel Production 19.34 30.40 57% -16% 41% 95%

2.C.2 Ferroalloys Production NA NA NA NA NA NA

2.C.3 Aluminium production NA NA NA NA NA NA

2.C.4 Magnesium production NO NO NO NO NO NO

2.C.5 Lead Production 19.16 0.00 -100% <1% 41% <1%

2.C.6 Zinc production NO NO NO NO NO NO

2.C.7 Other metal production 0.00 0.00 40% <1% <1% <1%

2.C.7.a Copper production 0.00 0.00 40% <1% <1% <1%

2.C.7.b Nickel production NO NO NO NO NO NO

2.C.7.c Other metals NA NA NA NA NA NA

2.C.7.d Storage, handling and transport of metal products

NO NO NO NO NO NO


2.G Other product manufacture and use NA NA NA NA NA NA






3 AGRICULTURE NA NA NA NA NA NA

5 WASTE 0.00 0.02 281% 4% <1% <1%




2.5 National emission total calculated on the basis of fuels used

According to Article 2 of NEC Directive 2016/2284, the Directive covers emissions from all sources occurring in the territory of the Member States, their exclusive economic zones and pol-lution control zones. Austria is a landlocked country and fuel prices significantly vary between neighbouring countries. Fuels tend to be sold in the territories where fuel prices are lower and they are exported to (and used in) other countries. Austria has experienced a considerable amount of ‘fuel export’ in the last few years; this needs to be taken into account when reporting emissions occurring in the Austrian territory.

For this reason Austria has chosen the usage of the national emission totals on the basis of fuels used (not including ‘fuel exports’) as a basis for compliance with the 2010 emission ceil-ings under the NEC Directive. Further details regarding ‘fuel exports’ are provided below in this chapter.

The approach in the Austrian inventory is as follows: After calculating fuel consumption for in-land road transport and off-road transport using a bottom-up approach (NEMO, GEORG), the sum of this fuel used is compared with the total fuel sold from the national energy balance (for details see 1.A.3.b Road Transport). The difference is then allocated to fuel export, which in-cludes fuel consumption for ground activities at airports and harbors as well, including fuel con-sumption by unregistered vehicles. As the fuel consumption reported under fuel export is in-cluded in the national totals, an underestimation of emissions can be excluded.

Table 63 presents the national emission totals of SO2, NOx, NMVOC and NH3 calculated on the basis of fuels used.

Table 63: Austria’s emissions 1990–2018 calculated on the basis of fuels used.

Austria’s Air Emissions not including ‘fuel exports’ [kt] SO2 NOx NMVOC NH3

1990 72.90 199.91 329.26 61.68

1991 69.66 201.55 317.68 62.40

1992 53.15 193.58 298.52 60.94

1993 51.64 185.07 280.44 61.96

1994 46.14 180.89 260.05 61.95

1995 45.85 180.09 244.98 63.06

1996 43.18 180.48 236.83 62.53

1997 39.97 180.78 223.70 62.86

1998 34.97 179.10 213.05 63.10

1999 33.27 179.21 203.49 62.04

2000 31.04 178.87 179.43 60.71

2001 31.81 181.89 172.54 60.64

2002 30.70 181.62 165.43 59.63

2003 30.43 186.13 161.23 59.52

2004 26.54 186.03 148.32 59.35

2005 25.90 189.41 152.63 59.24

2006 26.75 190.95 155.93 59.74

2007 23.41 187.28 151.77 61.05

2008 20.30 180.60 146.55 60.80



Austria’s Air Emissions not including ‘fuel exports’ [kt] SO2 NOx NMVOC NH3

2009 14.76 168.03 133.31 62.22

2010 16.00 168.18 133.44 62.19

2011 15.20 166.85 128.40 61.72

2012 14.83 162.72 126.10 62.04

2013 14.40 159.61 120.34 62.16

2014 14.51 155.79 113.64 62.94

2015 13.95 153.92 110.48 63.72

2016 13.28 150.00 108.85 64.52

2017 12.81 143.42 109.94 65.39

2018 11.73 135.74 106.55 64.38

Trend 90–18 -83.9% -32.1% -67.6% 4.4%

Figure 36: SO2, NOx, NMVOC and NH3 emissions not including ‘fuel exports.

SO2 emissions

In 2018, SO2 emissions amounted to 11.7 kt (not including ‘fuel exports‘). Since 1990 (72.9 kt), emissions have decreased continuously.

SO2 emissions (not including ‘fuel exports‘) have decreased since 1990 by 83.9%. This decline is mainly caused by a reduction of the sulphur content in mineral oil products and fuels (accord-ing to the Austrian Fuel Ordinance), the installation of desulphurisation units in plants (according to the Clean Air Act for boilers) and an increased use of low-sulphur fuels like natural gas. The

0

50

100

150

200

250

300

350

0

10

20

30

40

50

60

70

80

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

NO

x and

NM

VOC

[kt]

SO2 a

nd N

H3 [

kt]

Year

Emissions not including 'fuel exports'

SO2 NH3 Nox NMVOCSO2

Source: Umweltbundesamt NH

3 NO

x



economic crisis in 2009 caused a decrease in emissions, followed by an increase due to the re-covery of the economy. The strong reduction in emissions between 1991 and 1992 can be ex-plained by reduced coal consumption in power plants (1.A.1.a) and a reduction of SO2 emis-sions from oil fired power plants (1.A.1.a) as well as from iron and steel (1.A.2.a) and pulp and paper (1.A.2.d) production.

From 2017 to 2018 SO2 emissions (not including ‘fuel exports‘) decreased by 1.1 kt (– 8.4%). This was mainly caused by reductions in emissions from iron and steel (1.A.2.a, – 0.62 kt).

NOx emissions

In 1990, NOx emissions without ‘fuel exports’ amounted to 199.9 kt, and in 2018 to 135.7 kt.

Since 1990, NOx emissions (not including ‘fuel exports‘) have decreased by 32.1%. The reduc-tion in NOx emissions from 1991 to 1993 was mainly due to reductions in sector 1.A.3.b (pas-senger cars), sector 1.A.1.a (large oil and coal power plants) and sector 2.B.10.a (chemicals in-dustries). The economic crisis caused a decrease in emissions from 2008 to 2009.

From 2017 to 2018 the downward trend in NOx emissions (not including ‘fuel exports‘) continued with a decrease of 7.7 kt (– 5.4%). This was caused by the decline in road traffic, especially of passenger cars (1.A.3.b.1) (-2.1kt) and heavy duty vehicles (1.A.3.b.3) (-1.6kt). The main share of the national NOx emissions originates from fuel combustion. Road transport accounted for the biggest share of Austria's total NOx emissions in the year 2018 with a contribution of 48.3%, not including ‘fuel exports’.

NMVOC emissions

NMVOC emissions without ‘fuel exports’ amounted to 329.3 kt in 1990, and to 106.6 kt in 2018. This represents a reduction of 67.6%. From 2017 to 2018 NMVOC emissions (not including ‘fuel exports‘) decreased by 3.4 kt (– 3.1%).

Since 1990, the largest reductions were achieved in the road transport sector due to an increased use of catalytic converters and diesel cars. Currently the transport sector contributes only a small share of 5% of total NMVOC emissions.

Reductions in the solvent sector were achieved due to various regulations (Solvent Ordinance, Cogeneration Act, VOC Emissions Ordinance). In 2018, this sector accounted for around 28% of total NMVOC emissions. Compared to the previous year, emissions fell slightly by 1%.

The agriculture sector accounted for the largest share of NMVOC emissions at 34%. Here emissions fell by 1% compared with 2017.

Residential stationary heating accounts for 21% of the total and has declined by 8% compared to 2017, mainly due to the warm weather.

In particular, outdated mixed-fuel wood boilers continue to be the main reason for the relatively high emissions.

NH3 emissions

NH3 emissions without ‘fuel exports’ amounted to 61.7 kt in 1990, and to 64.4 kt in 2018.

Since 1990, NH3 emissions (not including ‘fuel exports‘) have increased by 4.4%. Austria's NH3 emissions arise almost entirely from the agriculture sector (93.8%). There have been only slight changes in the emissions since 1990. The slight increase in NH3 emissions (in spite of a de-



crease in the number of cattle) can be explained by an increase in loose housing systems (to ensure animal welfare and according to EU law) and an increase of high-capacity dairy cows. Additionally, there has been an increase in the use of urea as nitrogen fertiliser (a cost-efficient but otherwise less efficient fertiliser).

From 2017 to 2018 NH3 emissions (not including ‘fuel exports‘) decreased by 1.0 kt (–1.5%). The main reason is the lower amount of mineral fertilizer, in particular urea, which was applied on agricultural soils. Furthermore, the livestock numbers of cattle (dairy cows and other cattle) and swine were falling. However, the decrease of dairy cows was compensated with the rising milk yield.

Emissions from ‘fuel export’ In the year 2004, a study74 was commissioned to analyse the effects of fuel price differences between Austria and its neighbouring countries, including the so-called ‘fuel export’ effect, which means that fuel which is sold in Austria is used abroad. Relevant calculations were based on extensive questionnaires (addressed to truckers at the border, truckage companies), results from the Austrian transport model, and traffic counts. The importance of ‘fuel exports’ was confirmed by an update of the study in 2008/200975.

The following Table 64 provides information on the quantities of emissions that can be attributed to fuel exports in vehicle tanks.

Table 64: Emissions from ‘fuel exports’.

Emissions [Kilotonnes] SO2 NOx NMVOC NH3

1990 0.80 17.31 4.75 0.05 1991 1.06 25.19 10.63 0.17 1992 1.04 21.73 6.18 0.13 1993 1.18 21.70 4.23 0.11 1994 1.05 17.68 2.17 0.06 1995 0.96 17.79 1.60 0.05 1996 0.75 35.20 0.37 -0.08 1997 0.43 21.12 -0.69 -0.13 1998 0.66 34.58 1.53 0.02 1999 0.47 26.22 0.00 -0.13 2000 0.53 32.23 0.36 -0.13 2001 0.64 39.92 1.55 0.02 2002 0.69 48.07 3.52 0.35 2003 0.74 54.77 4.51 0.55 2004 0.06 54.56 4.51 0.60 2005 0.05 56.74 4.49 0.63

74 HAUSBERGER, S. & MOLITOR, R. (2004): Assessment of the effects of fuel tourism on fuel consumption and CO2 emission trends in Austria (in German). TU Graz by order of the Austrian Ministry of Life, not published. Graz, 2004.

75 HAUSBERGER, S.& MOLITOR, R. (2009): Assessment of the effects of fuel tourism on fuel consumption and CO2 emission trends in Austria (in German). TU Graz by order of the Austrian Federal Ministry of Agriculture, Forestry, Environment and Water Management and the Austrian Federal Ministry of Transport, Innovation and Technology, not published. Graz, 2009.



Emissions [Kilotonnes] SO2 NOx NMVOC NH3

2006 0.04 45.13 3.33 0.59 2007 0.04 41.28 3.04 0.60 2008 0.03 34.52 2.38 0.51 2009 0.03 33.06 2.21 0.51 2010 0.04 33.97 1.97 0.49 2011 0.03 27.17 1.52 0.41 2012 0.03 26.15 1.33 0.37 2013 0.04 28.45 1.22 0.33 2014 0.03 23.64 0.99 0.28 2015 0.03 22.44 0.96 0.29 2016 0.04 20.30 0.88 0.29 2017 0.04 18.53 0.79 0.28 2018 0.04 15.12 0.67 0.26

In 2018, about 10% of the reported NOx emissions were due to ‘fuel exports’. NOx-Emissions from fuel export increased between 1990 and 2005 (228%). From then emissions show a falling trend which is in line with decreasing activities (amount of fuel consumption) from 2005 onwards and improved specific NOx emissions per kilometer in each vehicle fleet category (diesel cars showing the smallest decrease with 11%). Especially NOx after treatment systems of trucks are working very well. In the model NEMO fuel export is allocated to truck traffic (35%) and passen-ger car traffic (65%). In 2018, NOx emissions of total fuel export were 13% below the level of 1990. For more details, please also refer to chapter 3.2.6.

Austria’s Informative Inventory Report (IIR) 2020 – Energy (NFR Sector 1)


3 ENERGY (NFR SECTOR 1)

Sector 1 Energy considers emissions originating from fuel combustion activities (NFR 1.A) 1.A.1 Energy Industries 1.A.2 Manufacturing Industries and Construction 1.A.3 Transport 1.A.4 Other Sectors (commercial and residential) 1.A.5 Other (Military)

as well as fugitive emissions from fuels (NFR 1.B) 1.B.1 Solid fuels 1.B.2 Oil and natural gas.

3.1 NFR 1.A Stationary Fuel Combustion Activities

3.1.1 General description

This chapter gives an overview of category 1.A Stationary Fuel Combustion Activities. It includes information on completeness, QA/QC and planned improvements as well as on emissions, emission trends and methodologies applied (including emission factors).

Information is also provided in the Austrian National Inventory Report (UMWELTBUNDESAMT 2020a) which is part of the submission under the UNFCCC. Additionally to information provided in this document, Annex 2 of (UMWELTBUNDESAMT 2020a)

includes further information on the underlying activity data used for emissions estimation. It describes the national energy balance (fuels and fuel categories, net calorific values) and the methodology of how activity data are extracted from the energy balance (correspondence of energy balance to SNAP and IPCC categories).

National energy balance data is presented in Annex 4 of (UMWELTBUNDESAMT 2020a).

3.1.1.1 Completeness

Table 65 provides information on the status of emission estimates of all sub categories. A “” indicates that emissions from this sub category have been estimated.



Table 65: Completeness of “1.A Stationary Fuel Combustion Activities”.

NFR Category

NO

x

CO

NM

VOC

SOx

NH

3

TSP

PM10

PM2.

5

Pb

Cd

Hg

DIO

X

PAH

HC

B

PCB


NE(3)

1.A.1.b Petroleum refining

IE(1)


IE(4)

IE(4)

IE(4)

IE(4)

IE(4)

IE(4)

IE(4)

IE(4)

IE(4)

IE(4)

IE(4)

IE(4)

IE(4)

IE(4)

IE(4)

1.A.2.a Iron and Steel

IE(5)

IE(5)

IE(5)

IE(5)

IE(5)

IE(5)

IE(5)

IE(5)

IE(5)

IE(5)

1.A.2.b Non-ferrous Metals

1.A.2.c Chemicals

1.A.2.d Pulp, Paper and Print

1.A.2.e Food Processing, Beverages and Tobacco

1.A.2.f Non-metallic Minerals

(7)

(7)

(7)

1.A.2.g Other Stationary combustion

1.A.3.e.1 Pipeline compressors

1.A.4.a.1 Commer-cial/Institutional: stationary

1.A.4.b.1 Residential: stationary

1.A.4.c.1 Agriculture/ Forestry/Fishing, Stationary

1.A.5.a Other, Stationary (including Military)

IE(2) IE(2) IE(2) IE(2) IE(2) IE(2) IE(2) IE(2) IE(2) IE(2) IE(2) IE(2) IE(2) IE(2) IE(2

)

(1) NMVOC emissions from Petroleum Refining are included in 1.B. (2) Emissions from military facilities are included in 1.A.4.a. (3) NH3 slip emissions from NOx control are not estimated. (4) Emissions from coke ovens are included in 1.A.2.a or 2.C.1. Emissions from final energy use of coal mines are

included in 1.A.2.g. (5) Heavy metals, POPs and PM emissions from integrated iron and steel plants are included in 2.C.1. (7) PM emissions from cement and lime kilns are included in 2.A.1 and 2.A.3.



Table 66 shows the correspondence of NFR and SNAP categories.

Table 66: NFR and SNAP categories of “1.A Stationary Fuel Combustion Activities”.

NFR Category SNAP


0101 0102

Public power District heating plants

1.A.1.b Petroleum refining 0103 Petroleum refining plants


0104 010503 010504

Solid fuel transformation plants Oil/Gas Extraction plants Gas Turbines

1.A.2.a Iron and Steel 0301 030302 030326

Comb. In boilers, gas turbines and stationary engines (Iron and Steel Industry) Reheating furnaces steel and iron Processes with Contact-Other(Iron and Steel Industry)

1.A.2.b Non-ferrous Metals 0301 030324

Comb. In boilers, gas turbines and stationary engines (Non-ferrous Metals Industry) Nickel production (thermal process)

1.A.2.c Chemicals 0301 Comb. in boilers, gas turbines and stationary engines (Chemicals Industry)

1.A.2.d Pulp, Paper and Print 0301 Comb. in boilers, gas turbines and stationary engines (Pulp, Paper and Print Industry)


0301 Comb. in boilers, gas turbines and stationary engines (Food Processing, Beverages and Tobacco Industry)

1.A.2.f Non-metallic Minerals

030311 030312 030313 030317 030319 030320 030323

Cement Lime Asphalt concrete plants Glass Bricks and Tiles Fine ceramic materials Magnesium production (dolomite treatment)

1.A.2.g Other Stationary Combustion

0301

Comb. in boilers, gas turbines and stationary engines (Industry not included in 1.A.2.a to 1.A.2.f)

1.A.3.e Other transportation 010506 Pipeline Compressors 1.A.4.a.1 Commercial/Institutional:

stationary 0201 Commercial and institutional plants

Open Fire pits and Bonfires 1.A.4.b.1 Residential: stationary 0202 Residential plants

Barbecue 1.A.4.c.1 Agriculture/

Forestry/Fishing: Stationary

0203 Plants in agriculture, forestry and aquaculture



3.1.1.2 Key Categories

Key category analysis is presented in Chapter 1.5. This chapter includes information on the En-ergy (stationary) sector. Key sources within this category are shown in Table 67.

Table 67: Key sources of sector Energy (stationary).

IPCC Category Category Name Pollutant KS-

Assessment

1.A.1.a Public Electricity and Heat Production SO2, NOx, Cd, Pb, Hg2), DIOX, TSP, PM10, PM2.5 LA, TA

1.A.1.b Petroleum refining Cd LA, TA 1.A.2.a Iron and Steel SO2, CO LA, TA 1.A.2.b Non-ferrous Metals - - 1.A.2.c Chemicals - - 1.A.2.d Pulp, Paper and Print SO2, Cd, Pb, Hg LA, TA 1.A.2.f Non-metallic Minerals SO2, NOx, Hg LA, TA

1.A.2.g.viii Other Stationary Combustion in Manufacturing Industries and Construction SO2, DIOX

LA, TA

1.A.4.a.1 Commercial/Institutional: Stationary PM2.5 LA, TA

1.A.4.b.1 Residential: stationary SO2, NOx, NMVOC, CO, Cd, Pb, Hg, PAH, DIOX, HCB, TSP, PM10, PM2.5

LA, TA

1.A.4.c.1 Agriculture/Forestry/Fishing: Stationary PAH, HCB1), PM2.5 LA, TA

LA = Level Assessment (if not further specified – for the years 1990 and 2018)

TA = Trend Assessment 2018 Note: 1)only TA, 2)only LA

3.1.1.3 Uncertainty Assessment

The table below gives an overview of uncertainties for sector Energy (stationary) for selected pollutants. The method used for the assessment of uncertainty is according to the EMEP/EEA air pollutant emission inventory guidebook 2016 (EEA 2016). Further information on the uncer-tainty assessment of activity data can be found in Austria`s National Inventory Report (UMWELT-BUNDESAMT 2020a). Where no specific information on uncertainties of emission factors was available, an average of the default values, based on the definitions of the qualitative ratings given in the EMEP/EEA Emission Inventory Guidebook 2016 is used (see chapter 1.7).

Table 68: Combined uncertainties for NOx, SO2, NMVOC, NH3 and PM2.5 for Energy (stationary).

NFR Categories NOx Emissions

[%]

NH3 Emissions

[%]

NMVOC Emissions

[%]

SO2 Emissions

[%]

PM2.5 Emissions

[%] 1.A.1.a Public Electricity and

Heat Production 21.54 750.04 200.16 21.54 60.53

1.A.1.b Petroleum refining 10.05 750.00 - 10.05 40.01 1.A.1.c Manufacture of Solid

fuels and Other Energy Industries

40.05 750.00 200.01 125.02 40.05

1.A.2.a Iron and Steel 11.18 750.02 200.06 11.18 125.10 1.A.2.b Non-ferrous Metals 40.31 750.02 200.06 20.62 125.10 1.A.2.c Chemicals 40.31 750.02 200.06 20.62 125.10 1.A.2.d Pulp, Paper and Print 41.23 750.07 200.25 22.36 125.40




[%]

NH3 Emissions

[%]

NMVOC Emissions

[%]

SO2 Emissions

[%]

PM2.5 Emissions

[%] 1.A.2.e Food Processing, Bever-

ages and Tobacco 40.31 750.02 200.06 20.62 125.10

1.A.2.f Non-metallic Minerals 40.31 750.02 200.06 20.62 125.10 1.A.2.g.7 Mobile Combustion in

Manufacturing Industries and Construction

40.01 125.00 40.01 20.02 40.01

1.A.2.g.viii Other Stationary Combus-tion in Manufacturing In-dustries and Construction

41.23 125.40 41.23 22.36 60.83

1.A.4.a Commercial/Institutional 40.31 125.10 70.18 20.62 60.21 1.A.4.b Residential 42.72 125.90 71.59 25.00 61.85 1.A.4.c Agriculture/Forestry/ Fis-

heries 100.12 125.10 100.12 20.62 100.12

1.A.5 Other 125.00 200.00 125.00 40.01 125.00

3.1.2 Methodological issues

General Methodology for stationary sources of NFR categories 1.A.1 to 1.A.5

For large point sources in categories 1.A.1.a, 1.A.1.b, 1.A.2.a, 1.A.2.d and 1.A.2.f (cement in-dustry) emission measurements of NOx, SO2, NMVOC, CO and TSP are the basis for the reported emissions. The remaining sources (area sources), where measured (plant-specific) emission data and plant specific activity data is not available, were estimated by multiplying the fuel consumption of each sub category taken from the national energy balance with a fuel and technology dependent emis-sion factor. Fuel specific emission factors are mainly country specific and taken from national studies.

Emission factors Emission factors are expressed as: mass of released pollutant per TJ of burned fuel (e.g. [kg/TJ]).

Emission factors may vary over time for the following reasons: The chemical characteristics of a fuel category varies, e.g. sulphur content in residual oil. The mix of fuels of a fuel category changes over time. If the different fuels of a fuel category

have different calorific values and their share in the fuel category changes, the calorific value of the fuel category might change over time. If emission factors are in the unit kg/t the trans-formation to kg/TJ induces a different emission factor due to varying net calorific values.

The (abatement-) technology of a facility – or of facilities – changes over time. Sources of NOx, SO2, VOC, CO, and TSP emission factors have been periodically published re-ports (BMWA 1990), (BMWA 1996), (UMWELTBUNDESAMT 2001a), (UMWELTBUNDESAMT 2004a). In these studies emission factors are provided for the years 1987, 1995 and 1996. Emission factors are mainly based on country specific measurements. NH3 emission factors are taken from a na-tional study (UMWELTBUNDESAMT 1993) and (EEA 2006, chapter B112). Details are included in the relevant chapters. As there is no information on the average sulphur content of natural gas, a Tier 1 method has been used and a SO2 emission factor of 0.3 kg/TJ has been applied for all categories of station-ary combustion and natural gas in case that plant specific information was not reported. The emission factor has been selected from the EMEP/EEA 2016 Guidelines chapter 1.A.4, table 3.13.



PCB emission factors PCB emission factors for coal and gasoil are selected from the EMEP/EEA 2016 Guidebook. The PCB emission factor of 3600 µg/t for residual fuel oil has been selected from (KAKAREKA et al. 2004) and converted to 85 µg/GJ.

The PCB emission factors for biofuels and waste have been derived from the ratio of Dioxin and PCB emission factors according to the measurements undertaken by (HEDMAN et al. 2006). A ratio of 0.09 g PCB per g Dioxin has been selected. The same ratio has also been selected for refinery fuels.

NH3

Emission factors are constant for the whole time series.

SO2, NOx, NMVOC, CO

For the years 1990 to 1994, emission factors are linearly interpolated by using the emission fac-tors from 1987 and 1995 taken from the studies mentioned above. From 1997 onwards, mainly the emission factors of 1996 are used.

In several national studies only emission factors for VOC are cited. NMVOC emissions are cal-culated by subtracting a certain share of CH4 emissions from VOC emissions.

Characteristic of oil products According to a national standard, residual fuel oil is classified into 3 groups with different sul-phur content (heavy, medium, light). Consumption of special residual fuel oil with a sulphur con-tent higher than 1% is limited to special power plants ≥ 50 MW and the oil refinery. Heating fuel oil is mainly used for space heating in small combustion plants. The following Table shows the sulphur contents of oil products which decreased strongly since 1980 due to legal measures. The years presented in the table are the years where legal measures came into force.

Table 69: Limited sulphur content of oil product classes according to the Austrian standard „ÖNORM”.

Year Residual fuel oil “Heavy”

Residual fuel oil “Medium”

Residual fuel oil “Light”

Heating fuel oil

1980 3.5% 2.5% 1.50% 0.8%

1981 0.5%

1982 1.5% 0.75%

1983 3.0% 0.3%

1984 2.5%; 2.0% 1.0% 0.50%

1985

1987 0.6%

1989 0.30% 0.2%

1990 0.20% 0.1%

1992 1.0%

1994 0.4%

Since the year 2008 a new gasoil product was introduced in Austria with a maximum sulphur content of 10 ppm (0.001%) which has the same quality as transport diesel. In the inventory it is assumed that the new product has a 100% market share since 2009 because of its lower taxes.



Activity data

A description of methodology and activity data will be provided in (UMWELTBUNDESAMT 2020a). If the energy balance reports fuel quantities by mass or volume units the fuel quantities must be converted into energy units [TJ] by means of net calorific values (NCV) which are provided by Statistik Austria along with the energy balance (IEA 2019). Not all categories of the gross inland fuel consumption are combusted or relevant for the inventory: Emissions from international bunker fuels are not included in the National Total but reported

separately as Memo Item. Avoiding of activity data double counting: transformation and distribution losses and trans-

formations of fuels to other fuels (like hard coal to coke oven coke or internal refinery pro-cesses which have been added to the transformation sector of the energy balance) is not considered as activity data.

Non-energy use is also not considered for calculation of emissions in Sector 1.A Energy. However, from these fuels fugitive emissions might occur which are considered in Sector 2.D.3 Solvents. Emissions from fuel used as a feedstock are considered in Sector 2 Industrial Processes.

Measured emissions

In case that measured emissions are used for inventory preparation it is essential that the cor-respondent activity data be additionally reported to avoid double counting of emissions within the inventory. Plant or industrial branch specific emissions are mostly broken down to fuel specif-ic emissions per NFR source category. In case that complete time series of measured emission data are not available implied emission factors are used for emission calculation. Implied emission factors may also be used for validation of measured emissions. Specific note to the uncertainty as addressed in the EU large combustion plants directive (LCP-D)

According to the Austrian legislation, operators have to report monthly or yearly emission loads. The validated averaged values are only used for checking the compliance with the limits, which have been set by the authorities. It is not expected that operators are misunderstanding this in a way that operators subtract any uncertainty from the measured emission concentrations when calculating emission loads, which are not subject of any legislative limitation and not relevant for any permit. In case of waste incineration, plant operators have been informed during the law preparation process to report the measured concentrations. Therefore it is not expected that any systematic under estimation occurs when using yearly reported emission loads in the inven-tory.

3.1.3 NFR 1.A.1 Energy Industries

NFR Category 1.A.1 comprises emissions from fuel combustion for public electricity and heat production (NFR 1.A.1.a), in petroleum refining (NFR 1.A.1.b), and in manufacture of solid fuels and other energy industries (NFR 1.A.1.c).

General Methodology

The following Table 70 gives an overview of methodologies and data sources of sub category 1.A.1 Energy Industries.



Table 70: Overview of 1.A.1 methodologies for main pollutants.

Activity data Reported/measured emissions

Emission factors

1.A.1.a boilers ≥ 50 MWth Reporting Obligation: fuel consumption (monthly). 2005–2018: ETS data

Reporting Obligation: NOx, SO2, TSP, CO (monthly) (About 130 boilers)

NMVOC, NH3: national studies

1.A.1.a boilers < 50 MWth Energy balance 2005–2018: ETS data for plants ≥ 20 MWth

Used for deriving emission factors

All pollutants: national studies

1.A.1.b (1 plant)

Reported by plant operator (yearly) 2005–2018: ETS data

Reported by plant operator: SO2, NOx, CO, NMVOC (yearly)

NH3: national study

1.A.1.c Energy balance 2005–2018: ETS data

Main pollutants and Dioxin: national studies Other Pollutants: EMEP/EEA 2016 GB

For 2005–2018, activity data from the emission trading system (ETS) are considered. ETS data fully covers category 1.A.1.b, covers about 90% of category 1.A.1.a fossil fuels and about 15% (from 2013 on about 70%) of category 1.A.1.c.

3.1.3.1 NFR 1.A.1.a Public Electricity and Heat Production

In this category, large point sources are considered. Until the year 2007, the Umweltbundesamt operated a database called „Dampfkesseldatenbank” (DKDB) which stored plant specific monthly fuel consumption as well as measured CO, NOx, SOx and TSP emissions from boilers with a thermal capacity greater than 3 MWth from 1990 to 2006. Since 2007 the reporting has been changed to an online system (EDM). To reach consistency with the GHG inventory all ETS plants and additionally 13 waste incineration boilers/kilns are considered as large point sources. These data are used to generate a split of the categories Public Power and District Heating into the two categories ≥ 300 MWth and ≥ 50 MWth to 300 MWth. Currently about 130 boilers are considered in this approach. It turned out that this methodology is appropriate for most cases but overall fuel consumption has to be checked against the national energy balance or other available complete datasets/surveys (see section on QA/QC).

Fuel consumption in the public electricity sector varies strongly over time. The most important reason for this variation is the fact that in Austria up to 78% of yearly electricity production comes from hydropower. If production of electricity from hydropower is low, production from thermal power plants is high and vice versa.

The following table shows the gross electricity and heat production of public power and district heating plants. Increasing district heat production is mainly generated by new biomass (local) heat plants and by waste incineration. The share of combined heat and power plants (CHP generation) is increasing and leads to higher efficiency of energy generation. The year 2010 shows a historic maximum of about 19 TWh of electricity production and the year 2017 shows a maximum of 76.6 PJ district heat production from fuel combustion.



Table 71: Public gross electricity and heat production.

Public gross electricity production [GWh] Public Heat Production [TJ] by Combustible

Fuels

Total Hydro1) Combustible Fuels

Geothermal Solar Wind

1990 43 403 30 111 13 292 0 0 0 24 427 1991 43 497 30 268 13 229 0 0 0 29 038 1992 42 848 33 530 9 318 0 0 0 27 601 1993 44 809 35 070 9 738 0 1 0 30 428 1994 44 804 34 078 10 725 0 1 0 30 729 1995 47 580 35 431 12 147 0 1 1 34 426 1996 45 953 32 892 13 055 0 1 5 44 483 1997 47 527 34 532 12 973 0 2 20 40 597 1998 47 789 35 596 12 146 0 2 45 43 415 1999 52 192 39 593 12 546 0 2 51 42 465 2000 52 810 41 131 11 609 0 3 67 42 197 2001 53 763 39 681 13 972 0 5 105 44 575 2002 54 385 40 597 13 636 3 9 140 45 056 2003 52 508 34 230 17 888 3 15 372 48 896 2004 56 051 37 700 17 397 2 18 934 51 786 2005 58 518 38 205 18 958 2 21 1 331 54 424 2006 55 898 36 907 17 212 3 22 1 753 54 730 2007 56 153 38 018 16 071 2 24 2 037 54 066 2008 57 842 39 458 16 341 2 30 2 011 60 794 2009 60 515 42 414 16 097 2 49 1 954 63 328 2010 61 571 40 500 18 916 1 89 2 064 70 415 2011 56 270 36 815 17 344 1 174 1 936 70 399 2012 64 030 47 204 14 025 1 337 2 463 74 061 2013 60 239 45 226 11 234 0 626 3 152 75 274 2014 57 742 44 270 8 840 0 785 3 846 69 707 2015 57 455 40 102 11 575 0 937 4 840 72 314 2016 60 429 42 482 11 617 0 1 096 5 235 74 159 2017 63 114 41 697 13 576 0 1 269 6 572 76 620 2018 60 610 40 742 12 400 0 1 438 6 030 73 110

1) including pumped storage; Source: IEA JQ 2019

As shown in Table 72 electricity supply increased by 13.2 TWh since 2000 of which approx. 80% has been supplied by additional imports until 2008. The year 2009 shows falling electricity con-sumption (supply) but an increase of production, mainly by hydropower. The year 2015 shows an historical maximum of net imports which contribute to 15% of total electricity supply.



Table 72: Electricity supply, gross production imports, exports and net imports [GWh].

Electricity [GWh] Supply1) Gross production2) Imports Exports Net Imports

1990 46 489 50 294 6 839 7 298 -459 1991 48 793 51 483 8 503 7 738 765 1992 48 197 51 190 9 175 8 621 554 1993 49 073 52 421 8 072 8 804 -732 1994 49 596 53 132 8 219 9 043 -824 1995 50 979 56 225 7 287 9 757 -2 470 1996 52 515 54 880 9 428 8 476 952 1997 53 069 56 704 9 008 9 775 -767 1998 54 039 57 001 10 304 10 467 -163 1999 55 167 60 944 11 608 13 507 -1 899 2000 55 750 61 257 13 824 15 192 -1 368 2001 58 338 62 449 14 467 14 252 215 2002 58 074 62 499 15 375 14 676 699 2003 60 058 60 174 19 003 13 389 5 614 2004 61 320 64 152 16 629 13 548 3 081 2005 62 948 66 833 20 355 17 732 2 623 2006 64 144 64 375 20 925 14 580 6 344 2007 64 762 65 085 21 783 15 767 6 016 2008 65 112 66 852 19 795 14 934 4 862 2009 62 783 69 088 19 542 18 762 780 2010 65 423 71 128 19 909 17 472 2 437 2011 65 602 65 813 24 977 16 777 8 199 2012 66 480 72 603 23 430 20 627 2 803 2013 67 088 68 357 24 960 17 689 7 270 2014 65 967 65 439 26 712 17 437 9 275 2015 67 051 65 299 29 389 19 328 10 062 2016 67 767 68 309 26 366 19 207 7 159 2017 68 848 71 324 29 362 22 817 6 546 2018 68 933 68 597 28 076 19 129 8 947

Source: IEA JQ 2019 1) Excluding own use and heat pumps, boilers and pumped storage use. Including losses 2) Public and auto producer gross production

Total fuel consumption data is taken from the energy balance (IEA JQ 2019) prepared by Statis-tik Austria. The remaining fuel consumption (= total consumption minus reported boiler con-sumption) is the activity data of plants < 50 MWth used for emission calculation with a Tier 2 methodology using national emission factors.

Table 73 shows activity data of category 1.A.1.a.



Table 73: Fuel consumption from NFR 1.A.1.a Public Electricity and Heat Production 1990–2018.

NFR 1.A.1.a 1.A.1.a 1.A.1.a 1.A.1.a 1.A.1.a 1.A.1.a Fuel liquid solid gaseous biomass other [PJ]

1990 143.14 15.99 61.40 59.46 1.63 4.66 1991 151.43 19.42 67.33 57.55 2.57 4.55 1992 117.37 18.86 39.97 49.50 3.00 6.05 1993 119.26 26.17 30.81 53.89 3.12 5.27 1994 124.03 24.09 32.97 58.28 3.39 5.29 1995 137.34 20.64 45.49 62.07 4.02 5.13 1996 160.38 19.96 47.52 79.65 6.12 7.12 1997 156.78 24.41 50.96 68.42 6.15 6.85 1998 150.06 28.13 35.81 73.53 6.81 5.78 1999 148.94 22.44 37.88 76.56 6.47 5.60 2000 141.01 15.84 49.16 62.51 8.05 5.46 2001 159.96 19.95 59.76 63.59 11.08 5.59 2002 155.61 10.42 56.12 69.22 13.07 6.77 2003 191.20 16.07 70.88 82.38 14.01 7.85 2004 188.33 14.92 69.06 78.93 15.34 10.09 2005 205.28 16.33 61.63 96.56 20.42 10.33 2006 198.15 14.54 60.20 80.80 29.54 13.08 2007 189.99 11.96 54.48 73.50 37.13 12.92 2008 199.99 11.60 47.87 83.32 44.09 13.11 2009 194.13 11.99 32.45 86.00 46.92 16.77 2010 218.97 9.78 41.47 94.55 55.30 17.86 2011 211.34 5.96 45.64 84.63 55.67 19.44 2012 195.21 3.07 37.18 75.07 60.01 19.88 2013 177.63 2.64 35.78 60.79 58.62 19.80 2014 157.60 2.19 24.74 50.63 58.31 21.73 2015 178.44 3.99 24.98 65.54 61.35 22.57 2016 177.68 5.59 16.91 71.80 59.05 24.32 2017 195.92 3.77 14.55 92.49 62.23 22.87 2018 174.77 1.46 14.78 79.34 57.19 21.99

Trend 1990–2018 22.1% -90.8% -75.9% 33.4% 3 412.9% 372.0%

Trend 2017–2018 -10.8% -61.2% 1.6% -14.2% -8.1% -3.8%

Boilers and gas turbines ≥ 50 MWth

This category considers steam boilers and gas turbines with heat recovery. Due to national reg-ulations, coal and residual fuel oil operated boilers are mostly equipped with NOx controls, flue gas desulphurisation and dust control units. A high share (regarding fuel consumption) of natural gas operated boilers and gas turbines are equipped with NOx controls. Emission data of boilers ≥ 50 MWth is consistent with data used for the national report to the Large Combustion Plant Di-



rective (LCP-D) 2001/80/EG (UMWELTBUNDESAMT 2006a) except in the case where gap filling was performed. An overview about installed SO2 and NOx controls and emission trends is presented in (UMWELTBUNDESAMT 2006a).

Emissions by fuel type are essential for validation and review purposes. If boilers are operated with mixed fuels derivation of fuel specific emissions from measured emissions is not always appropriate. Fuel specific emissions were derived as following: i Add up fuel consumption and emissions of the boiler size classes ≥ 300 MWth and ≥ 50 MWth

< 300 MWth. Convert fuel consumption from mass or volume units to TJ by means of average heating values from the energy balance.

ii Derive default emission factors for each fuel type of the “most representative” plants by means of actual flue gas concentration measurements and/or legal emission limits. This work is done by the Umweltbundesamt. The national “default” emission factors have been periodi-cally published in reports like (UMWELTBUNDESAMT 2004a).

iii Calculate “default” emissions by fuel consumption and national “default” emission factors. iv Calculate emission ratio of calculated emissions and measured emissions by boiler size class. v Calculate emissions by fuel type and boiler size class by multiplying default emissions with

emission ratio. Implied emission factors by fuel type may be calculated.

Table 74 shows emissions from LCP-D reporting and total 1.A.1.a emissions for selected years.

Table 74: 1.A.1.a total emissions, emissions from LCP-D reporting and share of LCP emissions for selected years

NOx (kt) SO2 (kt) PM10 (kt) CO (kt)

1A1a LCP LCP % 1A1a LCP LCP % 1A1a LCP LCP % 1A1a LCP LCP %

1990 12.13 10.98 91% 11.81 10.90 92% 0.78 0.69 88% 1.36 1.12 82%

1995 7.74 5.20 67% 5.95 3.03 51% 0.69 0.33 48% 1.72 1.18 68%

2000 7.10 5.29 75% 3.62 3.20 89% 0.49 0.24 48% 1.93 1.17 61%

2005 10.33 7.60 74% 3.36 2.88 86% 0.76 0.38 50% 2.55 1.29 51%

2010 11.17 5.39 48% 2.12 1.45 68% 1.21 0.21 18% 4.38 0.80 18%

2015 10.08 3.55 35% 1.20 0.60 50% 1.07 0.07 7% 4.21 0.58 14%

2016 9.32 2.99 32% 1.00 0.41 42% 1.00 0.05 5% 4.01 0.54 13%

2017 10.07 3.33 33% 0.97 0.36 37% 1.05 0.04 4% 4.21 0.55 13%

2018 8.92 3.01 34% 0.96 0.37 39% 0.99 0.03 3% 3.96 0.48 12%

In the approach above different coal types and residual fuel classifications are considered. Ta-ble 75 shows some selected aggregated results for 2018. The ratios of measured to calculated emissions show that the application of a simple Tier 2 Approach would introduce a high uncer-tainty for CO.



Table 75: NFR 1.A.1.a ≥ 50 MWth default emission factors fuel consumption and emissions ratios for the year 2018.

Fuel consumption [TJ]

NOx [kg/TJ]

CO [kg/TJ]

NMVOC [kg/TJ]

NH3 [kg/TJ]

NFR 1.A.1.a ≥ 50 MWth 0.80(1) 0.15(1)

SNAP 010101 0.75(1) 0.80(1)

Hard Coal 14.781 50.0 1.0 0.9 0.07(3)

Oil 2 26.0 3.0 5.0 2.68

Natural gas 60 400 30.0 4.0 0.06 1.0

Sewage sludge 10 100.0 200.0 38.0 0.02

Biomass 882 94.0 72.0 5.0 5.0

SNAP 010102 1.78(1) 0.62(1)

Natural gas 3 966 30.0 4.0 0.06 1.0

Waste 9 533 100.0 200.0 0.54(2) 0.02

SNAP 010201 11.96(1) 17.80(1)

Oil 13 100.0 4.0 5.0 2.68

Natural gas 1 374 25.0 4.0 0.5 1.0

SNAP 010202 0.37(1) 0.03(1)

Oil 392 85.0 4.0 5.0 2.68

Natural gas 5 304 25.0 4.0 0.5 1.0

Waste 12 461 48.0 200.0 0.54(2) 0.02

Sewage Sludge 640 100.0 200.0 38.0 0.02

(1) Emission ratio of measured emissions divided by calculated emissions. (2) EMEP/EEA 2016 Guidebook 5.C.1.a – table 3-1 (5.9 g/t). (3) Calculated from flue gas concentration (0.2 mg/Nm3).

Boilers and gas turbines < 50 MWth

Table 76 shows main pollutant emission factors used for calculation of emissions from boilers < 50 MWth for the year 2017. Increasing biomass consumption of smaller plants is a main source of NOx emissions from this category in 2018.

Table 76: NFR 1.A.1.a < 50 MWth main pollutant emission factors and fuel consumption for the year 2018.

Fuel Activity [TJ]

NOx [kg/TJ]

CO [kg/TJ]

NMVOC [kg/TJ]

SO2 [kg/TJ]

NH3 [kg/TJ]

Light Fuel Oil 78 159.4 10/45(1) 0.8 92 2.7

Heavy Fuel Oil 600 26/317.4(1) 3/15(1) 8.0 50/398(1) 2.7

Gasoil 115 65 10 4.8 0.5 2.7

Diesel oil 0 700 15 0.8 18.8 2.7

Liquified Petroleum Gas 260 150 5 0.5 6 1

Natural Gas/power and CHP 6 234 30 4 0.5 0.3 1

Natural Gas/district heating 2 065 41 5 0.5 0.3 1

Solid Biomass 47 356 94 72 5.0 11 5

Biogas, Sewage Sludge Gas, Landfill Gas

7 622 150 4 0.5 NA 1

(1) Different values for: Electricity & CHP/District heating.



Sources of emission factors

Sources of NOx, SO2, VOC, CO, and TSP emission factors are periodically published reports (BMWA 1990), (BMWA 1996), (BMWA 2003), (UMWELTBUNDESAMT 2004a). These reports provide information about the methodology of emission factor derivation and are structured by SNAP nomenclature. Emission factors for electricity and heat plants are based on expert judgment by Umweltbundesamt and experts from industry.

The NOx emission factor for biomass boilers ≤ 50 MWth and municipal solid waste is taken from a national unpublished study (UMWELTBUNDESAMT 2006b). Biomass NOx EFs are derived by means of measurements of 71 Boilers which have been selected as a representative sample from the approximately 1000 existing biomass boilers in 2005. Municipal waste NOx EFs are de-rived from plant specific data taken from (BMLFUW 2002b).

NH3 emission factors for coal, oil and gas are taken from (UMWELTBUNDESAMT 1993). For waste the emission factor of coal is selected. NH3 emission factors for biomass are taken from (EMEP/ CORINAIR 2006, chapter B112) and a value of 5 kg/TJ was selected.

VOC emission factors are divided into NMVOC and CH4 emission factors as shown in Table 77. The split follows closely (STANZEL et al. 1995).

Table 77: Share of NMVOC emissions in VOC emissions for 1.A.1.a.

Solid Fossile Liquid Fossile Natural Gas Biomass

Electricity plants 90% 80% 25% 75%

District Heating plants Hard coal 70% Brown Coal 80%

80% 30% 75%

3.1.3.2 NFR 1.A.1.b Petroleum Refining

In this category, emissions from fuel combustion of a single petroleum refining plant are consid-ered. The plant did not have any secondary DeNOX equipment until 2006, but a certain amount of primary NOx control has been achieved since 1990 by switching to low NOx burners (UMWELT-BUNDESAMT 2006b). SO2 reduction is achieved by a regenerative Wellman-Lord process facility (WINDSPERGER & HINTERMEIER 2003). Particulates control is achieved by two electrostatic precipi-tator (ESP) units. CO emissions were significantly reduced between 1990 and 1991 due to recon-struction of a FCC facility (UMWELTBUNDESAMT 2001a). Since 2007 the plant is equipped with a SNOX facility which reduces SO2 by about 65% and NOx emissions by about 55%.

The Austrian association of mineral oil industry (Fachverband der Mineralölindustrie) communi-cates yearly fuel consumption, SO2, NOx, CO, VOC and TSP emissions to the Umweltbundesamt (FVMI 2019). NMVOC emissions from fuel combustion are reported together with fugitive emis-sions under category 1.B.2.a. NH3, heavy metals and POPs emissions are calculated by means of emission factors and activity data. The following Table 78 shows the fuel consumption of the refinery.



Table 78: Fuel consumption from NFR 1.A.1.b Petroleum Refining 1990–2018.

NFR 1.A.1.b 1.A.1.b 1.A.1.b 1.A.1.b 1.A.1.b 1.A.1.b Fuel liquid solid gaseous biomass other [PJ]

1990 35.82 27.93 - 7.88 - - 1991 36.21 26.84 - 9.37 - - 1992 35.80 27.27 - 8.53 - - 1993 38.56 28.68 - 9.88 - - 1994 37.13 30.20 - 6.93 - - 1995 34.65 27.05 - 7.61 - - 1996 40.23 31.85 - 8.38 - - 1997 40.77 32.03 - 8.74 - - 1998 39.61 31.29 - 8.32 - - 1999 33.36 26.83 - 6.52 - - 2000 33.76 27.23 - 6.53 - - 2001 33.72 28.06 - 5.66 - - 2002 35.81 30.71 - 5.10 - - 2003 37.43 32.25 - 5.17 - - 2004 40.20 31.69 - 8.51 - - 2005 40.33 31.00 - 9.32 - - 2006 40.60 31.92 - 8.68 - - 2007 41.13 32.96 - 8.18 - - 2008 40.47 31.34 - 9.13 - - 2009 38.88 34.71 - 4.16 - - 2010 39.29 30.29 - 9.00 - - 2011 39.84 30.84 - 9.00 - - 2012 39.76 32.01 - 7.75 - - 2013 39.33 32.54 - 6.79 - - 2014 37.71 31.77 - 5.95 2015 38.77 32.74 - 6.03 - - 2016 37.59 34.38 - 3.21 - - 2017 38.23 31.07 - 7.16 - - 2018 39.20 32.17 7.02

Trend 1990–2018 9.4% 15.2% 10.9%

Trend 2017–2018 2.5% 3.5% -1.9%

Sources of emission factors NH3 emission factors for petroleum products (2.7 kg/TJ) and natural gas (1 g/TJ) are taken from (UMWELTBUNDESAMT 1993). Facility specific 1990 to 1998 emissions are presented in (UMWELTBUNDESAMT 2000a) and (UM-WELTBUNDESAMT 2001a). Cd emissions are calculated by means of the methodology from CONCAWE (CONCAWE 2017). For catalytic crackers, a Cd emission factor of 0.0000625 kg/m3 fresh feed has been used. The capacity of the cracker is about 1.4 Mt/year.



3.1.3.3 NFR 1.A.1.c Manufacture of Solid fuels and Other Energy Industries

This category includes emissions from natural gas combustion in the oil and gas extraction sector, natural gas refining, natural gas compressors for natural gas storage systems as well as own energy use of gas works which closed in 1995. Furthermore, PM emissions of charcoal kilns are included in this category. Emissions from final energy consumption of coal mines are included in category 1.A.2.g. Emis-sions from coke ovens are included in category 1.A.2.a.

Emissions from this category are presented in the following table.

Fuel consumption is taken from the national energy balance. Emissions are calculated with the simple CORINAIR methodology.

Table 79: Fuel consumption from NFR 1.A.1.c Manufacture of Solid fuels and Other Energy Industries 1990–2018.

NFR 1.A.1.c 1.A.1.c 1.A.1.c 1.A.1.c Fuel Liquid Gaseous Biomass

[PJ]

1990 9.23 0.062 9.13 0.03

1991 9.94 0.040 9.87 0.03

1992 9.45 0.000 9.42 0.03

1993 7.69 0.002 7.65 0.03

1994 8.20 0.001 8.17 0.03

1995 11.06 0.007 11.02 0.03

1996 4.74 - 4.71 0.03

1997 5.03 - 5.00 0.03

1998 6.39 - 6.36 0.03

1999 5.13 - 5.10 0.03

2000 5.10 - 5.07 0.03

2001 4.45 - 4.42 0.03

2002 3.86 - 3.83 0.03

2003 3.07 - 3.04 0.03

2004 4.46 - 4.43 0.03

2005 7.14 - 7.10 0.03

2006 4.76 - 4.73 0.04

2007 4.80 - 4.76 0.04

2008 4.31 - 4.28 0.04

2009 4.81 - 4.77 0.04

2010 4.34 - 4.30 0.04

2011 4.83 - 4.80 0.04

2012 3.76 - 3.72 0.04

2013 4.55 - 4.52 0.04

2014 4.50 - 4.47 0.04

2015 4.99 - 4.95 0.04

2016 4.94 - 4.90 0.04



NFR 1.A.1.c 1.A.1.c 1.A.1.c 1.A.1.c Fuel Liquid Gaseous Biomass

[PJ]

2017 4.71 - 4.68 0.03

2018 4.36 4.32 0.04

Trend 1990–2018 -52.7% -100.0% -52.7% 26.4%

Trend 2017–2018 -7.4% - -7.6% 12.4%

Emission factors and activity data 2018

Table 80 summarizes the selected emission factors for main pollutants and activity data for the year 2018. It is assumed that emissions are uncontrolled.

Table 80: NFR 1.A.1.c main pollutant emission factors and fuel consumption for the year 2018.

Fuel Source of NOx, CO, NMVOC, SO2 emission factors(1)

Activity [TJ]

NOx [kg/TJ]

CO [kg/TJ]

NMVOC [kg/TJ]

SO2 [kg/TJ]

NH3 [kg/TJ]

Natural Gas/Oil gas extraction and Gasworks

(BMWA 1990) 4 363 150.0 10.0 0.5 0.3 1.0

Residual fuel oil/ Gasworks (BMWA 1996) 0(2) 235.0 15.0 8.0 398.0 2.7

Liquid petroleum gas/Gasworks (BMWA 1990) 0(2) 40.0 10.0 0.5 6.0 1.0

(1) Default emission factors for industry are selected (2) Gasworks closed in 1995

NH3 emission factors are taken from (UMWELTBUNDESAMT 1993).

PM emissions from charcoal production

It has been assumed (WINIWARTER et al. 2007) that charcoal is produced in traditionally kilns by approximately 20 producers. Assuming 10 charges per producer and year each of 50 m³ wood input , assuming an output of 200 kg of charcoal from 1 000 kg of wood input and assuming a density of 350 kg/m³ wood leads to an estimated activity of 1 000 t charcoal per year which is 31 TJ (net calorific value 31 MJ/kg charcoal). Applying an emission factor of 2.2 kg TSP/GJ charcoal which is similar to brown coal stoker fired furnaces this leads to an emission of approx. 70 t TSP per year. Furthermore it is assumed that 100% of particles are PM2.5. Char coal pro-duction data is taken from the national energy balance which is 1.4 kt in 2018.

The following Table 81 shows activity data for charcoal.



Table 81: Char coal production activity data 1990‒2018.

Year Char coal production (t) Year Char coal production (t)

1990 1 000 2004 1 000

1991 1 000 2005 1 101 1992 1 000 2006 1 220 1993 1 000 2007 1 149 1994 1 000 2008 1 253 1995 1 000 2009 1 365 1996 1 000 2010 1 181 1997 1 000 2011 1 130 1998 1 000 2012 1 377 1999 1 000 2013 1 269 2000 1 000 2014 1 263 2001 1 000 2015 1 447 2002 1 000 2016 1 382 2003 1 000 2017 1 222

- - 2018 1 375

3.1.3.4 Emission factors for heavy metals

Coal

Values were taken from the CORINAIR Guidebook (1999), Page B111-58, Table 31:

For 1985, two thirds of the values for “DBB, Dust Control” were selected (from the ranges given in the guidebook the mean value was used). For 1995, the value for “DBB, Dust Control + FGD” was selected, as in these 10 years the existing dust controls were supplemented with flue gas de-sulphurisation. For the years in between the values were linearly interpolated.

The net calorific value used to convert values given in [g/Mg fuel] to [g/MJ fuel] was 28 MJ/kg for hard coal and 10.9 MJ/kg for brown coal.

Due to the legal framework, most coal fired power plants were already equipped with dust control and flue gas desulphurisation in 1995, and no substantial further improvements were made since then. Thus, the emission factor for 1995 was used for the years onwards.

The cadmium emission factor of brown coal is derived from a flue gas concentration of 6 µg/m³ (UMWELTBUNDESAMT 2003b).

Fuel oil

The emission factors base on the heavy metal content of oil products of the only Austrian refin-ery that were analysed in 2001 (see Table 82). It is assumed that imported oil products have a similar metal content.

Table 82: Heavy Metal Contents of Fuel Oils in Austria.

[mg/kg] Cadmium Mercury Lead

Heating Oil < 0.01 < 0.003 < 0.01

Light fuel oil < 0.01 < 0.003 < 0.01

Heavy fuel oil (1%S) 0.04 < 0.003 < 0.01



Only for heavy fuel oil a value for the heavy metal content was quantifiable, for lighter oil prod-ucts the heavy metal content was below the detection limit. As the heavy metal content depends on the share of residues in the oil product the emission factor of medium fuel oil was assumed to be half the value of heavy fuel oil. For light fuel oil and heating and other gas oil one fifth and one tenth respectively of the detection limit was used.

As legal measures ban the use of heavy fuel oil without dust abatement techniques and the emission limits were lower over the years it was assumed that the emission factor decreased from 1985–1995 by 50%, except for Mercury where dust abatement techniques do not effect emissions as efficiently as Mercury is mainly not dust-bound.

The emission factors for “other oil products” (which is only used in the refinery) are based on the following assumption: the share of Cd and Pb in crude oil is about 1% and 2%, respectively. The share of this HM – in particulate emissions of the refinery – was estimated to be a fifth of the share in crude oil, which results in a share of 0.2% and 0.4% of dust emissions from the refin-ery. Based on a TSP emission factor of about 5.7 g/GJ, the resulting emission factors for Cd and Pb are 10 mg/GJ and 20 mg/GJ.

For Mercury, 10 times the EF for heavy fuel oil for category 1.A.1.a was used.

For 1985, twice the value as for 1990 was used.

Other Fuels

For fuel wood the value from (OBERNBERGER 1995) for plants > 4 MW was used for 1985 and 1990. For 1995 and for wood waste, for the whole time series, the value taken from personal in-formation about emission factors for wood waste from the author was used.

For plants < 50 MW the emission factor for industrial waste is based on measurements of Aus-trian plants (FTU 2000).

The emission factors for the years 1985–1995 for municipal waste and sewage sludge base on regular measurements at Austrian facilities (MA22 1998). For industrial waste and for plants > 50 MW, emission factors were based on (EPA 1998, CORINAIR 1997, EPA 1997, EPA 1993, WINIWARTER 1993, ORTHOFER 1996); improvements in emission control have been considered.

The emission factors for waste (municipal and industrial waste and sewage sludge, for plants > 50 MW and for the year 2004 were taken from (BMLFUW 2002b).

Natural Gas

Heavy metal emission factors of natural gas are selected from the EMEP/EEA Guidebook 2016, table 3-17.

Table 83: Cd emission factors for Sector 1.A.1 Energy Industries.

Cadmium EF [mg/GJ] 1985 1990 1995 2010 Coal 102A Hard coal 0.1548 0.1140 0.073 0.073 105A Brown coal 2.13 (all years) Oil 204A Heating and other gas oil 2050 Diesel

0.02 (all years)

203B Light fuel oil 0.05 (all years) 203C Medium fuel oil 0.5 (all years) 203D Heavy fuel oil 1.0 0.75 0.5 0.5 110A Petrol coke 224A Other oil products

20 10 10 10



Other Fuels 111A Fuel wood 116A Wood waste

6.1 6.1 2.5 2.5

115A Industrial waste (< 50MW) 7 (all years) 1.A.1.c Natural gas 301A Natural gas 0.0012 (all years)

The following table presents Cd emission factors of several waste categories. Emission factors 2006 are derived from measurements (UMWELTBUNDESAMT 2007).

Table 84: Cd emission factors for waste for Sector 1.A.1 Energy Industries.

Cadmium EF [mg/t Waste] 1985 1990 1995 2010 114B Municipal waste 2 580 71 12 11 115A Industrial waste (> 50 MW) 720 510 30 4.5 118A Sewage sludge – 235 19 5.2

Table 85: Hg emission factors for Sector 1.A.1 Energy Industries.

Mercury EF [mg/GJ] 1985 1990 1995 2010 Coal 102A Hard coal 2.98 2.38 1.8 1.8 105A Brown coal 7.65 6.12 4.6 4.6 Oil 204A Heating and other gas oil 2050 Diesel

0.007 (all years)

203B Light fuel oil 0.015 (all years) 203C Medium fuel oil 0.04 (all years) 203D Heavy fuel oil 0.075 (all years) 110A Petrol coke 224A Other oil products

0.75 (all years)

Other Fuels 111A Fuel wood 1.9 (all years) 116A Wood waste (> 50 MW) 1.9 (all years) 115A Industrial waste (< 50 MW) 2.0 (all years) Natural gas 301A Natural gas (1.A.1.c) 0.1 (all years)

The following table presents Hg emission factors of several waste categories. Emission factors 2006 are derived from measurements (UMWELTBUNDESAMT 2007).

Table 86: Hg emission factors for waste for Sector 1.A.1 Energy Industries.

Mercury EF [mg/t Waste] 1985 1990 1995 2010 114B Municipal waste 1 800 299 120 25.2 115A Industrial waste (> 50 MW) 100 112 49 15.5 118A Sewage sludge – 55 9 9



Table 87: Pb emission factors for Sector 1.A.1 Energy Industries.

Lead EF [mg/GJ] 1985 1990 1995 2010 Coal 102A Hard coal 13.33 11.19 9.1 9.1 105A Brown coal 1.93 1.44 0.96 0.96 Oil 204A Heating and other gas oil 2050 Diesel

0.02 (all years)

203B Light fuel oil 0.05 (all years) 203C Medium fuel oil 0.12 (all years) 203D Heavy fuel oil 0.25 0.19 0.13 0.13 110A Petrol coke 224A Other oil products

20 (all years)

Other Fuels

111A Fuel wood 26.3 26.3 21.15 21.15 116A Wood waste: Public Power [0101] 21 (all years) 116A Wood waste: District Heating [0102] 50 (all years) 115A Industrial waste (< 50 MW) 50 (all years) Natural gas 301A Natural gas (1.A.1c) 0.0015 (all years)

The following table presents Hg emission factors of several waste categories. Emission factors 2006 are derived from measurements (UMWELTBUNDESAMT 2007).

Table 88: Pb emission factors for waste for Sector 1.A.1 Energy Industries.

Lead EF [mg/t Waste] 1985 1990 1995 2010

114B Municipal waste 30 000 1 170 150 36

115A Industrial waste (> 50 MW) 8 300 2 400 10 10

118A Sewage sludge – 730 6 6

3.1.3.5 Emission factors for POPs

Fossil fuels

The dioxin (PCDD/F) emission factor for coal and gas were taken from (WURST & HÜBNER 1997), for fuel oil the value given in the same study and new measurements were considered (FTU 2000).

The HCB emission factor for coal was taken from (BAILEY 2001).

The PAK emission factors are based on results from (UBA BERLIN 1998), (BAAS et al. 1995), (ORTHOFER & VESELY 1990) and measurements by FTU.

PCB emission factors have been selected as outlined in chapter 3.1.3.

The 1.A.1.c (SNAP 010503 and 010504) natural gas emission factor for PAK4 is selected from the EMEP/EEA Guidebook 2016, table 3-17.



Other fuels

The dioxin (PCDD/F) emission factor for wood is based on measurements at Austrian plants > 1 MW (FTU 2000).

The PAK emission factors are based on results from (UBA BERLIN 1998) and (BAAS et al. 1995).

Gasworks Default national emission factors of industrial boilers were selected. For 224A Other Oil Prod-ucts the emission factors of 303A LPG were selected.

Table 89: POPs emission factors for Sector 1.A.1 Energy Industries.

EF PCDD/F [µg/GJ]

HCB [µg/GJ]

PAK4 [mg/GJ]

PCB [µg/GJ]

Coal Coal (102A, 105A, 106A) 0.0015 0.46 0.0012 0.0033 Fuel Oil

Fuel Oil (203B, 203C, 203D, 204A) exc. Gasworks, 110A Petrol coke

0.0004 0.08 0.16 0.00013

203D Heavy fuel oil in gasworks 0.009 0.12 0.24 85 224A Other oil products in gasworks 0.0017 0.14 0.011 85 308A Refinery gas 0.0006 0.04 NA 0.000054 Gas 301A, 303A Natural gas and LPG exc. SNAP 010202, 010301

0.0002 0.04 NA NA

301A, 303A Natural gas and LPG, SNAP 010202, 010301

0.0004 0.08 NA 0.000036

301A 010503, 010504, 010506 0.0002 0.04 0,0116 0.000018 Other Fuels 114B Municipal Waste 115A Industrial waste/unspecified

0.0051 14.5 0.17 0.0005 0.0008

Biomass

111A Wood (> 1 MW) 116A Wood waste (> 1 MW)

0.01 2.0 0.2 0.0009

111A Wood (< 1 MW) 116A Wood waste (< 1 MW)

0.14 28.0 2.4 0.0009

116A Wood waste/Straw 0.12 24.0 3.7 0.0009 309A, 309B, 310A Gaseous biofuels 0.0006 0.072 0.032 NA

Waste emissions factors are expressed as per ton of dry substance and derived from plant spe-cific measurements (HÜBNER 2001b, HÜBNER et al. 2002, UMWELTBUNDESAMT 2007). Comma separated values indicate plant specific emissions factors. The PCDD/F emission factor for 2014 onwards has been derived from measurements of 9 waste incineration plants (UMWELTBUNDES-AMT 2019c).



Table 90: POP emission factors for Sector 1.A.1 Energy Industries.

EF PCDD/F [µg/t] HCB [µg/t] PAK4 [mg/t] 114B Municipal Waste 0.09/0.044(1) 247.0 0.7; 0.13 115A Industrial waste 0.21/0.044(1) 126.0 0.16 118A Sewage Sludge 0.09/0.044(1) 20.0 0.09

(1) First value for 2000-2013; second value for 2014 onwards.

3.1.3.6 Emission factors for PM

As already described in chapter 1.4 the emission inventories of PM for different years were pre-pared by contractors and incorporated into the inventory system afterwards.

Large point sources (LPS)

In a first step large point sources (LPS) are considered. For the reporting years up to 2006 the UMWELTBUNDESAMT was operating a database to store plant specific data, called „Dampfkessel-datenbank” (DKDB) which includes data on fuel consumption, NOx, SOx, CO and PM emissions from boilers with a thermal capacity greater than 3 MWth for all years from 1990 onwards. From the reporting year 2007 on this database has been replaced by a web based reporting system (EDM76) operated by the ministry of environment. These data are used to generate a split of the categories Public Power and District Heating, with further distinction between the two categories ≥ 300 MWth and ≥ 50 MWth to 300 MWth of thermal capacity. Currently about 60 power and dis-trict heating plants with 120 boilers and 9 waste incineration plants with 14 boilers/kilns are con-sidered with this approach. From the year 2007 on fuel consumption of large point sources is taken from the emission trading system (ETS) which considers facilities which a total boiler thermal capacity ≥ 20 MWth. The yearly emission declarations from the corresponding boilers are taken from the EDM.

The fuel consumption of all considered point sources is subtracted from the total consumption of this category, which is taken from the energy balance. The other combustion plants are consid-ered as area source.

For point sources ≥ 50 MW plant specific emission and activity data from the DKDB were used. The ‘implied emission factors’, which are calculated by division of emissions by activity data, are given in Table 91.

Emission factors from 2000 onwards for the fuel type wood waste were taken from (UMWELT-BUNDESAMT 2006a).

The PM10/TSP and PM2.5/TSP ratios were taken from (WINIWARTER et al. 2001).

76 http://edm.gv.at

http://edm.gv.at/



Table 91: PM implied emission factors (IEF) for LPS in NFR 1.A.1 Energy Industries.

TSP IEF [g/GJ] %PM10 %PM2.5 1990 1995 2000 2018 [%] [%]

Public Power (0101)(1) 5.51 3.34 2.74 0.27 95 80 District Heating (0102) (1) 3.58 1.37 0.73 0.22 95 80 Petroleum Refining (010301)(2) 4.3 2.8 3.4 1.2 95 80 Wood waste (116A) 55 55 22 22 90 75

(1) Used fuels: Hard coal(102A), Lignite(105A), Log wood(111A), Industrial waste(115A), Sewage sludge(118A), Residual fuel oil(203B, 203C, 203D and Natural gas(301)

(2) Used fuels: Refinery gas (308A), FCC coke (110A), Residual fuel oil (203D), LPG (303A), Other oil products (224A) and Natural gas (301A)

Area sources

In a second step the emissions of the area source are calculated. Emissions of plants < 50 MW are calculated by multiplying emission factors with the corresponding activity. Coal and gas

The emission factors for coal and gas were taken from (WINIWARTER et al. 2001) and are valid for the whole time series. Oil

The emission factor for high-sulphur fuel (203D) medium-sulphur fuel (203C) and low-sulphur fuel (203B) base on an analysis of Austrian combustion plants regarding limit values (TSP: 70 mg/Nm³, 60 mg/Nm³ and 50 mg/Nm³) (UMWELTBUNDESAMT 2006a), these values were used for all years.

The emission factor for heating and other gas oil (204A) was taken from (WINIWARTER et al. 2001) and used for all years. 77

For diesel the emission factors for heavy duty vehicles and locomotives as described in chapter 3.2.6 were used. Other Fuels Emission factors for wood and wood waste (111A and 116A), MSW renewable, MSW non-renewable and industrial waste (114B and 115A) and low-sulphur fuel (203B) for the years 1990 and 1995 were taken from (WINIWARTER et al. 2001), for the years afterwards an updated value from (UMWELTBUNDESAMT 2006a) has been used.

The emission factor for biogas, sewage sludge gas and landfill gas (309B and 310A) were taken from (WINIWARTER et al. 2001) and used for all years.

The shares of PM10 and PM2.5 were taken from (WINIWARTER et al. 2001).

77 as of central heating boilers in the residential sector (Hauszentralheizung – HZH)



Table 92: PM emission factors for combustion plants (< 50 MW) in NFR 1.A.1.

TSP Emission Factors [g/GJ] PM10 PM2.5

1990 1995 2000 2018 [%] [%] Gas

301A and 303A 0.50 90 75

Coal

102A 45.00 90 75

105A and 106.A 50.00 90 75

Oil

203B 16.00 90 75

203D 22.00 90 80

204A 1.00 90 80

224A 0.50 90 75

2050 50.00 100 100

Other Fuels

111A and 116A 55.00 55.00 22.00 22.00 90 75

114B and 115 A 9.00 9.00 1.00 1.00 95 80

309B and 310A 0.50 90 75

3.1.3.7 Category-specific Recalculations

Updates of activity data and of NCVs follow the updates of the IEA-compliant energy balance compiled by the federal statistics authority Statistik Austria (Chapter 3.1.9).

The most significant recalculations for the year 2017 took place for categories: 1.A.1.a: +0.7 kt NOx, +0.05 kt PM2.5 1.A.1.b: - 0.04 t Cd

Petroleum refining (1.A.1.b) Cd emissions from 1A1b refineries have been re-estimated using a method developed by CONCAWE (CONCAWE 2017). This results in higher Cd emissions 1990 but lower Cd emissions 2017.

3.1.4 NFR 1.A.2 Manufacturing Industry and Combustion

NFR Category 1.A.2 Manufacturing Industries and Construction comprises emissions from fuel combustion in the sub categories Iron and steel (NFR 1.A.2.a), Non-ferrous metals (NFR 1.A.2.b), Chemicals (NFR 1.A.2.c), Pulp, paper and print (NFR 1.A.2.d), Food processing, beverages and tobacco (NFR 1.A.2.e), Non-metallic Minerals (NFR 1.A.2.f) Mobile Combustion in Manufacturing Industries and Construction (NFR 1.A.2.g.7)78 Other Stationary Combustion in Manufacturing Industries and Construction (NFR 1.A.2.g.viii). 78 methodologies for mobile sources are described in Chapter 3.2.7.1



3.1.4.1 General Methodology

Table 93 gives an overview of methodologies and data sources of sub category 1.A.2 Manufac-turing Industry and Combustion. Reported/Measured emission data is not always taken one-to-one in cases that reported fuel consumption is not in line with data from energy balance. How-ever, in these cases data is used for emission factor derivation. For the reporting year 2005 on activity data from the emission trading system (ETS) has been considered for validation of the energy statistics and ETS activity data has been used for a breakdown by sectors of category 1.A.2.f.

Fuel consumption of Industrial Autoproducers is allocated to the relevant subcategories 1.A.2.a to 1.A.2.g, 1.A.1.b and 1.A.4.a.i.

Table 93: Overview of 1.A.2 methodologies for main pollutants.

Activity data Reported/Measured emissions Emission factors

1.A.2.a Iron and Steel – Integrated Plants (2 units)

Reported by plant operator (yearly).

Reported by plant operator: SO2, NOx, CO, NMVOC, TSP (yearly).

NH3: National study

1.A.2.a Iron and Steel – other Energy balance 2005–2017: ETS data.

All pollutants: National studies

1.A.2.b Non-ferrous Metals Energy balance 2005–2017: ETS data.


1.A.2.c Chemicals Energy balance 2005–2017: ETS data.

Waste incineration: SO2, NOX, CO, NMVOC, PM10


1.A.2.d Pulp, Paper and Print Energy balance 2005–2017: ETS data.

Reported by Industry Association: SO2, NOx, CO, NMVOC, TSP (yearly).

NOX, PM10, NH3: National studies


Energy balance 2005–2017: ETS data.


1.A.2.f Cement Clinker Production

National Studies 2005–2017: ETS data.

Reported by Industry Association: SO2, NOx, CO, NMVOC, TSP, Heavy Metals (yearly).

NH3: National study

1.A.2.f Glass Production Association of Glass Industry 2005–2017: ETS data.

Direct information from industry association: NOx, SO2.

CO, NMVOC, NH3: National studies

1.A.2.f Lime Production Energy balance 2005–2017: ETS data.


1.A.2.f Bricks and Tiles Production

Association of Bricks and Tiles Industry 2005–2017: ETS data.


1.A.2.g Other Energy balance 2005–2017: ETS data.


The SO2 emission factor for natural gas is selected from the EMEP 2016 Guidebook.

3.1.4.2 NFR 1.A.2.a Iron and Steel

In this category mainly two integrated iron and steel plants with a total capacity of about 6 Mt pig iron or 7.5 Mt of crude steel per year are considered. Facilities relevant for air emissions are blast furnaces, coke ovens, iron ore sinter plants, on site power plants, LD converters, rolling mills, scrap preheating, collieries and other metal processing. According to the SNAP and NFR no-menclatures these activities have to be reported to several sub categories. In case of the Aus-trian inventory emissions from above mentioned activities are reported in sub categories 1.A.2.a and 2.C. Heavy metals, POPs and PM emissions of the two integrated steel plants are included in category 2.C (SNAP 0402). Category 1.A.2.a also includes emissions from fuel combustion in other steel manufacturing industries.



Integrated steelworks (two units) Two companies report their yearly NOx, SO2, NMVOC, CO and PM emissions to the Umwelt-bundesamt. Environmental reports are available on the web at http://www.emas.gv.at under EMAS register-Nr. 221 and 216, which partly include data on air emissions. During the last years parts of the plants where reconstructed and equipped with PM emission controls which has also led to lower heavy metal and POP emissions. Reduction of SO2 and NOx emissions of in-plant power stations was achieved by switching from coal and residual fuel oil to natural gas.

Table 94: PM emission controls of integrated iron & steel plants.

Facility Controlled emissions

Plant 1 1,5 Mt/a crude steel

Iron ore sinter plant: PM: electro filter, fabric filter

Cast house/pig iron recasting PM

LD converter PM: electro filter

Ladle furnace PM: electro filter

Plant 2: 6 Mt/a crude steel

Iron ore sinter plant: 2 mio t/a sinter PM: “AIRFINE” wet scrubber

Coke oven: 1,9 mio t/a coke Coke transport and quenching: PM

Cast house PM

LD converter PM

Rolling mill PM

The following table shows emissions of main pollutants from the two integrated iron and steel plants.

Table 95: NFR 1.A.2.a – integrated iron and steel plants – reported main pollutant emissions.

NOx (kt) SO2 (kt) NMVOC (kt) CO (kt)

1990 4.97 6.05 0.07 210.68

1991 4.94 4.75 0.06 185.41

1992 4.14 3.25 0.05 226.91

1993 4.50 3.48 0.05 237.35

1994 4.18 3.79 0.06 250.57

1995 4.44 3.69 0.06 182.09

1996 4.20 4.20 0.06 206.61

1997 4.43 4.43 0.07 211.56

1998 4.45 4.46 0.07 197.77

1999 4.37 4.52 0.07 121.11

2000 4.18 4.06 0.09 164.47

2001 4.04 4.53 0.09 140.79

2002 4.30 4.71 0.09 134.37

2003 4.33 4.89 0.22 147.20

2004 4.10 4.50 0.26 153.14

2005 4.61 4.86 0.29 138.18

2006 4.69 5.31 0.31 147.90

2007 4.74 5.37 0.30 138.79

2008 4.56 4.76 0.27 124.65

http://www.emas.gv.at/



NOx (kt) SO2 (kt) NMVOC (kt) CO (kt)

2009 3.73 3.83 0.25 116.96

2010 4.15 4.72 0.24 107.79

2011 4.05 4.91 0.26 120.81

2012 4.06 5.03 0.26 120.62

2013 3.64 5.21 0.22 125.26

2014 3.45 5.27 0.17 134.60

2015 3.78 5.36 0.18 145.63

2016 3.76 5.12 0.16 144.76

2017 3.42 4.79 0.22 144.94

2018 3.26 4.18 0.15 133.26

Other fuel combustion

Fuel combustion in other iron and steel manufacturing industry is calculated by the simple CORINAIR methodology. Activity data is taken from energy balance. The following tables summa-rize the selected emission factors for the main pollutants and activity data for the year 2018. It is assumed that emissions are uncontrolled.

Table 96: NFR 1.A.2.a – area source – main pollutant emission factors and fuel consumption for the year 2018.

Fuel Source of NOx, CO, NMVOC, SO2 emission factors

Activity [TJ]

NOx [kg/TJ]

CO [kg/TJ]

NMVOC [kg/TJ]

SO2 [kg/TJ]

NH3 [kg/TJ]

Hard coal (BMWA 1990) (1) 0 250.0 150.0 15.0 600.0 0.01

Coke oven coke (BMWA 1990) (1) 84 220.0 150.0 8.0 500.0 0.01

Residual fuel oil < 1% S (BMWA 1996) (1) 0 118.0 10.0 0.8 92.0 2.70

Residual fuel oil ≥ 1% S (BMWA 1996) (1) 74 235.0 15.0 8.0 398.0 2.70

Heating oil (BMWA 1996) (2) 0 65.0 15.0 4.8 45.0 2.70

Kerosene (BMWA 1996) (3) 0 118.0 15.0 4.8 92.0 2.70

Natural gas (BMWA 1996) (1) 6 589 41.0 5.0 0.5 0.3(6) 1.00

LPG (BMWA 1996) (4) 7 41.0 5.0 0.5 6.0(7) 1.00 (1) Default emission factors for industry (2) Default emission factors for district heating plants (3) Upper values from residual fuel oil < 1% S and heating oil (4) Values for natural gas are selected (5) Values for bark are selected (6) EMEP 2016 Guidebook 1.A.4.b.i – table 3-13. (7) From (LEUTGÖB et al. 2003)

NH3 emission factors are taken from (UMWELTBUNDESAMT 1993). PM, HM and POP emission factors are described in a separate section below.



3.1.4.3 NFR 1.A.2.b Non-ferrous Metals

This category enfolds emissions from fuel combustion in non-ferrous metals industry including heavy metal and POPs emissions from melting of products. Fuel consumption activity data is taken from the energy balance. Emissions from this category are presented in the following ta-bles.

This category also includes SO2, heavy metals and POPs emissions from secondary nickel pro-duction (SNAP 030324). SO2 and Hg emissions are plant specific and other pollutants are cal-culated by means of emission factors (see chapters 1.1.4.10 and 1.1.4.11).

Activity data

Fuel consumption is taken from (IEA JQ 2019).

Table 97: Fuel consumption from NFR 1.A.2.b Non-ferrous Metals 1990–2018.

NFR 1.A.2.b 1.A.2.b 1.A.2.b 1.A.2.b 1.A.2.b 1.A.2.b Fuel (PJ) liquid solid gaseous biomass other

1990 2.08 0.51 0.21 1.35 - -

1991 1.87 0.49 0.17 1.21 - -

1992 2.11 0.45 0.08 1.58 - -

1993 2.56 0.46 0.19 1.92 - -

1994 4.44 0.57 0.14 3.73 - -

1995 4.36 0.57 0.09 3.70 - -

1996 2.84 0.68 0.15 2.02 - -

1997 3.50 0.94 0.19 2.37 - -

1998 3.29 0.83 0.16 2.30 - -

1999 3.03 0.66 0.21 2.16 - -

2000 3.12 0.64 0.17 2.31 - -

2001 3.41 0.72 0.10 2.60 - -

2002 3.42 0.60 0.16 2.67 - -

2003 3.53 0.56 0.15 2.82 - -

2004 3.67 0.51 0.16 3.01 - -

2005 3.68 0.45 0.13 3.10 - -

2006 3.76 0.45 0.12 3.19 - -

2007 4.28 0.40 0.14 3.74 - -

2008 4.35 0.32 0.14 3.89 - -

2009 4.02 0.26 0.16 3.60 - -

2010 4.10 0.26 0.07 3.77 - -

2011 4.31 0.30 0.07 3.94 - -

2012 4.19 0.28 0.06 3.85 - -

2013 5.08 0.46 0.13 3.99 0.48 0.02

2014 4.89 0.43 0.15 4.26 0.03 0.01

2015 5.07 0.38 0.13 4.52 0.03 0.01



NFR 1.A.2.b 1.A.2.b 1.A.2.b 1.A.2.b 1.A.2.b 1.A.2.b Fuel (PJ) liquid solid gaseous biomass other

2016 5.28 0.27 0.13 4.83 0.03 0.02

2017 5.19 0.24 0.11 4.80 0.02 0.02

2018 5.87 0.10 0.10 5.63 0.03 0.01

Trend 1990–2018 182.4% -81.3% -52.5% 316.0%

Trend 2017–2018 13.2% -59.9% -8.9% 17.2% 87.5% -47.0%

The following Table 98 shows fuel consumption and main pollutant emission factors of category 1.A.2.b for the year 2018.

Table 98: NFR 1.A.2.b main pollutant emission factors and fuel consumption for the year 2018.


Activity [TJ]

NOx [kg/TJ]

CO [kg/TJ]

NMVOC [kg/TJ]

SO2 [kg/TJ]

NH3 [kg/TJ]




Heating oil (BMWA 1996) (2) 0 65.0 15.0 4.8 0.5(6) 2.70

Kerosene (BMWA 1996) (3) 0 118.0 15.0 4.8 92.0 2.70

Other liquid fuels Similar to 1.A.1.c Other liquid fuels 0

40.0 10.0 0.5 6.0 2.68

Natural Gas (BMWA 1996) (1) 5 628 41.0 5.0 0.5 0.3(7) 1.00

LPG (BMWA 1996) (4) 79 41.0 5.0 0.5 6.0(5) 1.00 (1) Default emission factors for industry (2) Default emission factors for district heating plants (3) Upper values from residual fuel oil < 1% S and heating oil (4) Values for natural gas are selected (5) From (LEUTGÖB et al. 2003) (6) 10 ppm sulphur content (7) EMEP 2016 Guidebook 1.A.4.b.i – table 3-13.

3.1.4.4 NFR 1.A.2.c Chemicals

Category 1.A.2.c includes emissions from fuel combustion in chemicals manufacturing industry. Because the inventory is linked with the NACE/ISIC consistent energy balance, plants which mainly produce pulp are considered in this category. Main polluters are pulp and basic anorganic chemicals manufacturers. Fuel consumption is taken from the energy balance (IEA JQ 2019). Main pollutant emission factors used for emission calculation are industrial boilers default values or derived from plant specific measurements (fluidized bed boilers).



Waste incineration

NOX, SO2, CO, NMVOC and PM10 emissions from a large waste incineration plant are plant specific.

Activity data


Table 99: Fuel consumption from NFR 1.A.2.c Chemicals 1990–2018.

NFR 1.A.2.c 1.A.2.c 1.A.2.c 1.A.2.c 1.A.2.c 1.A.2.c Fuel (PJ) liquid solid gaseous biomass other 1990 16.29 1.27 1.09 9.36 2.90 1.67

1991 16.09 1.33 1.41 8.33 2.90 2.12

1992 17.45 0.99 1.95 8.83 3.26 2.42

1993 17.81 1.18 1.96 10.89 2.18 1.60

1994 16.56 1.40 1.58 9.97 1.81 1.79

1995 17.11 1.34 1.58 10.33 1.72 2.15

1996 18.97 1.39 1.94 10.35 2.66 2.63

1997 20.38 1.88 2.66 10.87 2.91 2.05

1998 18.62 1.60 2.63 10.48 2.20 1.72

1999 25.52 1.14 3.24 14.65 4.98 1.51

2000 25.45 0.85 2.61 15.78 3.95 2.26

2001 23.96 1.20 2.65 15.46 1.84 2.81

2002 24.27 0.97 2.64 14.95 1.58 4.13

2003 26.73 1.06 2.62 15.11 2.11 5.82

2004 27.73 1.03 2.48 15.28 1.68 7.26

2005 24.45 0.98 1.57 18.04 2.43 1.43

2006 23.59 0.94 1.12 16.95 2.44 2.14

2007 22.56 1.03 0.84 16.40 2.93 1.35

2008 25.91 1.15 0.75 17.31 3.11 3.59

2009 25.85 1.60 0.74 17.82 2.49 3.21

2010 28.69 1.89 0.81 18.29 3.51 4.19

2011 27.69 1.68 0.72 18.35 3.25 3.69

2012 28.15 1.35 0.73 18.62 3.67 3.78

2013 26.22 1.10 0.88 18.04 3.35 2.86

2014 25.82 0.71 1.29 17.72 2.86 3.25

2015 26.10 0.75 1.08 18.15 3.06 3.06

2016 28.87 0.79 1.11 20.18 3.42 3.36

2017 30.03 0.73 2.17 20.51 3.59 3.02

2018 27.55 0.42 1.28 20.09 3.00 2.77

Trend 1990–2018 69.1% -67.1% 17.3% 114.5% 3.4% 66.2%

Trend 2017–2018 -8.3% -43.1% -41.3% -2.1% -16.5% -8.2%



Table 100 summarizes activity data and emission factors for 2018. Underlined values indicate non default emission factors.

Table 100: NFR 1.A.2.c main pollutant emission factors and fuel consumption for the year 2018.


Activity [TJ]

NOx [kg/TJ]

CO [kg/TJ]

NMVOC [kg/TJ]

SO2 [kg/TJ]

NH3 [kg/TJ]

Hard coal (BMWA 1990) (1) 1 276 80.3(5) 150.0 15.0 60.0(9) 0.01 Coke oven coke (BMWA 1990) (1) 0 220.0 150.0 8.0 500.0 0.01 Residual fuel oil < 1% S (BMWA 1996) (1) 84 118.0 10.0 0.8 92.0 2.70


Heating oil (BMWA 1996) (2) 15 65.0 15.0 4.8 0.5 2.70 Other liquid fuels Similar to 1.A.1.c

Other liquid fuels 94 40.0 10.0 0.5 6.0 2.68

Natural Gas (BMWA 1996) (1) 20 087 41.0 5.0 0.5 0.3(11) 1.00 LPG (BMWA 1996) (3) 9 41.0 5.0 0.5 6.0(4) 1.00 Industrial waste (BMWA 1990) (1) 2 775 29.4(6) 0.8(6) 0.54 6.9(6) 0.02 Solid biomass (BMWA 1996) (1) 2 653 100.0(7) 72.00 5.0 30.0 5.00 Biogas (BMWA 1990) (8) 351 150.0 5.0 0.5 NA 1.00

(1) Default emission factors for industry (2) Default emission factors for district heating plants (3) Values for natural gas are selected (4) From (LEUTGÖB et al. 2003) (5) 50% of hard coal is assigned to fluidized bed boilers in pulp industry with comparatively low EF. (6) Implied emission factor (7) Assumed to be consumed by one plant. The selected NOx emission factor is derived from plant specific data of the

DKDB. (8) Uncontrolled default emission factors for natural gas fired industrial boilers are selected. (9) For hard coal an uncontrolled SO2 emission factor of 600 kg/TJ with a control efficiency of 90% is assumed. (10) 10 ppm sulphur content (11) EMEP 2016 Guidebook 1.A.4.b.i – table 3-13.

3.1.4.5 NFR 1.A.2.d Pulp, Paper and Print

Category 1.A.2.d includes emissions from fuel combustion in pulp, paper and print industry. Plants which mainly produce pulp are considered in category 1.A.2.c Chemicals except black liquor recovery boilers. All black liquor recovery boilers are equipped with flue gas desulphuriza-tion and electrostatic precipitators. Additionally all fluidized bed boilers are equipped with elec-trostatic precipitators and/or fabric filters. A detailed description of boilers, emissions and emis-sion controls is provided in the unpublished study (UMWELTBUNDESAMT 2005b).

Fuel consumption is taken from the energy balance. SO2 emissions are taken from (AUSTRO-PAPIER 2002–2019). TSP emissions are taken from (UMWELTBUNDESAMT 2005a). Other main pol-lutant emission factors used for emission calculation are industrial boilers default values.

Activity data Fuel consumption is taken from (IEA JQ 2019).



Table 101: Fuel consumption from NFR 1.A.2.d Pulp, Paper and Print 1990–2018.

NFR 1.A.2.d 1.A.2.d 1.A.2.d 1.A.2.d 1.A.2.d 1.A.2.d Fuel liquid solid gaseous biomass other [PJ]

1990 55.31 10.94 4.13 17.01 23.03 0.19

1991 61.74 14.24 5.53 18.35 23.45 0.19

1992 56.44 8.53 4.71 18.49 24.45 0.26

1993 58.13 8.80 4.45 16.02 28.64 0.23

1994 70.01 8.39 3.81 27.11 30.38 0.32

1995 67.32 6.72 3.97 24.57 31.58 0.48

1996 66.37 5.13 3.87 28.24 28.32 0.81

1997 72.46 6.62 4.69 33.48 27.61 0.07

1998 70.14 5.60 4.68 31.56 28.24 0.07

1999 69.69 2.97 3.79 31.29 31.50 0.14

2000 67.11 2.20 4.70 31.83 28.38 0.00

2001 68.60 2.30 4.02 30.33 31.83 0.11

2002 64.16 1.96 4.83 29.53 27.71 0.12

2003 68.64 2.13 4.42 33.04 28.85 0.20

2004 66.79 1.70 4.63 30.64 29.57 0.25

2005 74.09 1.79 5.02 30.85 36.32 0.11

2006 72.45 1.63 5.23 28.81 36.63 0.15

2007 73.26 1.26 4.01 30.98 36.85 0.17

2008 72.27 1.07 3.68 31.94 35.49 0.10

2009 70.82 1.33 3.80 31.84 33.75 0.10

2010 75.30 0.93 3.55 34.91 35.84 0.08

2011 74.54 0.68 3.94 33.88 35.96 0.09

2012 70.48 0.51 3.95 29.86 36.10 0.06

2013 69.21 0.83 4.23 26.04 37.94 0.17

2014 65.39 0.44 4.19 23.63 36.95 0.18

2015 64.76 0.46 4.29 24.71 35.11 0.18

2016 66.21 0.32 4.38 24.69 36.68 0.15

2017 66.48 0.22 4.44 24.99 36.66 0.18

2018 69.51 0.18 4.15 27.37 37.51 0.29

Trend 1990–2018 25.7% -98.3% 0.4% 60.9% 62.9% 49.4%

Trend 2017–2018 4.6% -18.5% -6.5% 9.6% 2.3% 62.4%

Table 102 shows activity data and emission factors for 2017. SO2 emission factors were derived from national default values for industrial boilers taken from (BMWA 1990) and not highly repre-sentative for single fuels within this category. Black liquor recovery and fluidized bed boilers are fired with combined fuels and therefore NOx emission factors are not always representative for single fuel types. Underlined values indicate non default emission factors.



For the year 2017, NOX and TSP/PM10/PM2.5 emission factors are updated by means of a new study (WINDSPERGER2019) which is based on boiler specific data. Emission factors 2006-2016 are linearly interpolated.

Table 102: NFR 1.A.2.d main pollutant emission factors and fuel consumption for the year 2018.


Activity [TJ]

NOx [kg/TJ]

CO [kg/TJ]

NMVOC [kg/TJ]

SO2 [kg/TJ]

NH3 [kg/TJ]

Hard coal (BMWA 1990) (1) 4 152 75.0(9) 150.0 15.0 84.8 0.01

Brown coal (BMWA 1990) (1) 0 170.0 150.0 23.0 70.2 0.02

Brown coal briquettes (BMWA 1990) (1) 0 170.0 150.0 23.0 70.2 0.02




Heating oil (BMWA 1996) (2) 5 65.0 15.0 4.8 0.1 2.70

Kerosene (BMWA 1996) (6) 0 118.0 15.0 4.8 12.2 2.70

LPG (BMWA 1996) (3) 15 41.0 5.0 0.5 6.0(4) 1.00

Natural Gas (including lime kilns)

(BMWA 1996) (1) 27 374

46.9(9) 5.0 0.5 IE 1.00

Industrial waste (BMWA 1990) (1) 289 100.0 200.0 0.54 17.2 0.02

Black liquor (BMWA 1990) (1) 29 792 68.0(9) 20.0 4.0 17.2 0.02

Fuel wood (BMWA 1996) (8) 0 110.0 370.0 5.00 7.9 5.00

Solid biomass + Sewage sludge

(BMWA 1996) (1) 5 908

86.0(9) 72.00 5.0 7.9 5.00

Biogas (BMWA 1990) (5) 997 150.0 5.0 0.5 IE 1.00 (1) Default emission factors for industry (2) Default emission factors for district heating plants (3) Values for natural gas are selected (4) From (LEUTGÖB et al. 2003) (5) Uncontrolled default emission factors for natural gas fired industrial boilers are selected. (6) Upper values from residual fuel oil < 1% S and heating oil (7) NOx emission factor for black liquor is derived from partly continuous measurements according to

(UMWELTBUNDESAMT 2005a). (8) Emission factors of wood chips fired district heating boilers are selected. (9) From (WINDSPERGER 2019)).

3.1.4.6 NFR 1.A.2.e Food Processing, Beverages and Tobacco

Category 1.A.2.e includes emissions from fuel combustion in food processing, beverages and tobacco industry. Due to the low fuel consumption it is assumed that default emission factors of uncontrolled industrial boilers are appropriate although it is known that sugar factories operate some natural gas and coke oven coke fired lime kilns. It is assumed that any type of secondary emission control does not occur within this sector.



Activity data


Table 103: Fuel consumption from NFR 1.A.2.e Food Processing, Beverages and Tobacco 1990–2018.

NFR 1.A.2.e 1.A.2.e 1.A.2.e 1.A.2.e 1.A.2.e 1.A.2.e Fuel (PJ) liquid solid gaseous biomass other

1990 13.91 4.45 0.18 9.15 0.13 - 1991 14.76 5.11 0.20 9.33 0.12 - 1992 13.65 4.43 0.10 9.03 0.09 - 1993 13.97 4.99 0.20 8.62 0.15 - 1994 14.67 4.55 0.18 9.84 0.10 - 1995 15.10 4.40 0.06 10.53 0.10 - 1996 14.63 3.27 0.11 11.22 0.03 0.006 1997 17.08 4.02 0.13 12.91 0.02 0.006 1998 15.64 3.21 0.11 12.31 0.01 0.006 1999 14.28 2.14 0.08 11.83 0.22 - 2000 15.16 2.18 0.21 12.53 0.24 - 2001 15.74 3.13 0.12 12.22 0.27 - 2002 19.12 2.35 0.15 16.36 0.27 - 2003 16.03 2.94 0.15 12.71 0.23 - 2004 15.97 3.34 0.12 12.28 0.23 - 2005 16.51 3.19 0.13 12.71 0.48 - 2006 16.22 3.23 0.10 12.27 0.63 - 2007 15.61 2.77 0.11 12.02 0.72 - 2008 15.56 2.50 0.12 12.19 0.75 - 2009 15.98 2.71 0.14 12.44 0.69 0.0003 2010 16.97 2.68 0.14 13.52 0.63 0.0040 2011 16.95 2.65 0.15 13.47 0.67 0.0039 2012 16.97 2.08 0.16 13.87 0.86 0.0037 2013 15.90 0.97 0.15 14.23 0.55 0.0016 2014 16.48 1.15 0.17 14.59 0.56 0.0005 2015 16.29 0.90 0.22 14.52 0.64 0.0001 2016 14.82 0.77 0.15 13.34 0.56 0.0003 2017 14.62 0.64 0.17 13.36 0.45 0.0004 2018 14.23 0.46 0.13 13.10 0.54 0.0045

Trend 1990–2018 2.3% -89.7% -25.6% 43.2% 311.2% - Trend 2017–2018 -2.7% -28.8% -21.5% -1.9% 19.3% 1151.6%

Fuel consumption activity data is taken from the energy balance. Main pollutant emission fac-tors used for emission calculation are industrial boilers default values taken from (BMWA 1990).

Table 104 summarizes activity data and emission factors for 2018.



Table 104: NFR 1.A.2.e main pollutant emission factors and fuel consumption for the year 2018.


Activity [TJ]

NOx [kg/TJ]

CO [kg/TJ]

NMVOC [kg/TJ]

SO2 [kg/TJ]

NH3 [kg/TJ]

Hard coal (BMWA 1990) (1) 0 250.0 150.0 15.0 600.0 0.01

Brown coal (BMWA 1990) (1) 0 170.0 150.0 23.0 630.0 0.02

Brown coal briquettes (BMWA 1990) (1) 0 170.0 150.0 23.0 630.0 0.02




Heating oil (BMWA 1996) (2) 61 65.0 15.0 4.8 0.5 2.70

Kerosene (BMWA 1996) (6) 0 118.0 15.0 4.8 92.0 2,7

LPG (BMWA 1996) (3, 8) 179 41.0 5.0 0.5 6.0(4) 1.00

Natural Gas (BMWA 1996) (1) 13 098 41.0 5.0 0.5 0.3(9) 1.00

Industrial waste (BMWA 1990) (1) 4 100.0 200.0 0.54 130.0 0.02

Fuel wood (BMWA 1996) (7) 0 110.0 370.0 5.00 11.0 5.00

Solid biomass (BMWA 1996) (1) 352 143.0 72.00 5.0 60.0 5.00

Biogas (BMWA 1990) (5) 78 150.0 5.0 0.5 NA 1.00 (1) Default emission factors for industry (2) Default emission factors for district heating plants (3) Values for natural gas are selected (4) From (LEUTGÖB et al. 2003) (5) Uncontrolled default emission factors for natural gas fired industrial boilers are selected. (6) Upper values from residual fuel oil < 1% S and heating oil. (7) Emission factors of wood chips fired district heating boilers are selected. (8) According to a sample survey (WINDSPERGER et al. 2003) natural gas NOx emissions factors are in the range of 41

(furnaces) to 59 (boilers) kg/TJ. (9) EMEP 2016 Guidebook 1.A.4.b.i – table 3-13.

3.1.4.7 NFR 1.A.2.f Non-metallic Minerals

Category 1.A.2.f includes emissions from fuel combustion of furnaces and kilns of cement (SNAP 030311), lime (SNAP 030312), bricks/tiles (SNAP 030319) and glass manufacturing in-dustries (SNAP 030317) and magnesite sinter plants (SNAP 030323).

Table 105: Fuel consumption from NFR 1.A.2.f Non-metallic Minerals 1990–2018.

NFR 1.A.2.f.i 1.A.2.f.i 1.A.2.f.i 1.A.2.f.i 1.A.2.f.i 1.A.2.f.i Fuel (PJ) liquid solid gaseous biomass other

1990 23.34 6.26 5.69 10.09 - 1.31

1991 23.58 6.59 5.05 10.28 - 1.67

1992 23.29 5.76 6.28 9.37 - 1.88

1993 23.50 6.89 5.07 9.73 - 1.82

1994 23.97 7.82 3.98 10.22 - 1.94

1995 22.07 4.37 4.63 11.10 - 1.98

1996 22.97 3.32 5.55 11.93 - 2.17



NFR 1.A.2.f.i 1.A.2.f.i 1.A.2.f.i 1.A.2.f.i 1.A.2.f.i 1.A.2.f.i Fuel (PJ) liquid solid gaseous biomass other

1997 24.60 3.40 5.85 13.25 - 2.10

1998 24.58 3.41 5.63 12.87 - 2.66

1999 21.45 3.81 3.80 10.97 - 2.88

2000 22.79 2.32 5.34 11.58 - 3.56

2001 23.33 1.93 4.89 11.97 - 4.55

2002 25.06 3.29 3.62 13.59 - 4.56

2003 24.80 3.37 3.26 14.01 - 4.16

2004 27.60 4.46 3.03 14.77 - 5.34

2005 25.77 3.39 3.92 11.90 1.74 4.82

2006 27.23 2.54 5.71 11.54 1.56 5.89

2007 28.84 2.66 6.50 11.94 1.59 6.16

2008 28.61 2.45 6.13 11.59 3.34 5.10

2009 24.43 1.97 4.61 9.67 3.11 5.08

2010 24.26 2.17 3.33 10.86 2.87 5.04

2011 24.60 2.33 2.94 11.14 3.00 5.19

2012 24.27 1.87 3.06 10.55 3.25 5.53

2013 25.03 1.83 2.71 11.35 3.28 5.87

2014 25.83 1.69 2.88 11.48 3.28 6.51

2015 26.43 1.72 2.77 11.28 3.43 7.23

2016 26.69 1.81 2.29 11.64 3.45 7.50

2017 26.85 1.48 2.19 12.04 3.39 7.74

2018 27.82 1.41 2.41 12.10 3.70 8.20

Trend 1990–2018 19.2% -77.5% -57.7% 20.0% - 525.8%

Trend 2017–2018 3.6% -4.8% 9.7% 0.5% 9.0% 5.9%

Table 106 shows total fuel consumption and emissions of main pollutants for sub categories of 1.A.2.f Non-metallic Minerals for the year 2018.



Table 106: NFR 1.A.2.f Non-metallic Minerals - Fuel consumption and emissions of main pollutants by sub category for the year 2018.

Category Fuel Consumption [TJ]

NOx [kt]

CO [kt]

NMVOC [kt]

SO2 [kt]

NH3 [kt]

PM2.5 [kt]

SNAP 030311 Cement Clinker Production 13 821 2.31 5.35 0.21 0.32 0.119

Included in 2A1

SNAP 030312 Lime Production 2 759 0.78 0.12 0.01 0.18 0.002

Included in 2A2

SNAP 030317 Glass Production 3 332 0.56 0.02 0.00 0.16 0.003 0.001

SNAP 030319 Bricks and Tiles Production 2 954 0.76 0.09 0.01 0.18 0.005 0.034

SNAP 030323 Magnesia Production 4 949 1.38 0.14 0.01 0.07 0.005 0.033

Total 27 815 5.78 5.71 0.24 0.91 0.134 0.068

Cement clinker manufacturing industry (SNAP 030311)

Currently nine cement clinker manufacturing plants are operated in Austria. Some rotary kilns are operated with a high share of industrial waste. In 2006, all exhaust streams from kilns and product heat recovery units were controlled by electrostatic precipitators. All plants are using SNCR/SCR to reduce NOX emissions and one plant is equipped with a SO2 scrubber (MAUSCHITZ 2018). All plants are equipped with continuous emission measurement devices for PM, NOx and SOx, four plants with CO, two plants with TOC and one plant with a continuous Hg measurement device (MAUSCHITZ 2004). Annual activity data for 1990 to 2013 and emissions of 25 pollutants of all plants are estimated in periodic surveys (HACKL & MAUSCHITZ 1995, 1997, 2001, 2003, 2007), (MAUSCHITZ 2004, 2008, 2010–2019). Table 107 shows detailed fuel consumption data for 2018.

Table 107: Cement clinker manufacturing industry. Fuel consumption for the year 2018.

Fuel Activity [TJ] Hard coal 712

Brown coal 1 266

Petrol coke 444

Residual fuel oil < 1% S 21

Residual fuel oil 0.5% S 0

Residual fuel oil ≥ 1% S 55

Heating oil 12

Natural Gas 114

Industrial waste 8 128

Pure biogenic residues 3 068

Total 13 821



HCB accidental release

Within the period, 2012 to 2014 high amounts of HCB were released from a cement plant unin-tentionally79. The reason for release was the co-incineration of HCB contaminated material (lime) at temperatures that were too low to destroy the HCB. Around 97 kt of lime was incinerat-ed which contained about 586 kg of HCB of which 40% were released. It has to be noted that these assumptions are very uncertain due to the absence of measurements during this period. The underlying data for the assumptions was collected after authorities stopped plant operation and is mainly based on expert judgement.

The releases are estimated to be the following:

Table 108: HCB accidental releases for the years 2012, 2013 and 2014.

Year HCB (kg) 2012 24 2013 102 2014 108

Lime manufacturing industry (SNAP 030312)

This category includes emissions from natural gas fired lime kilns. From 1990 to 2004 it includes magnesit sinter plants because sector specific data is available from the year 2005 on only (ETS data). Natural gas consumption is calculated by subtracting natural gas consumption of glass manufacturing industry (SNAP 030317), bricks and tiles industry (SNAP 030319), magne-site sinter industry (SNAP 030323) and cement industry (SNAP 030311) from final consumption of energy balance category Non-metallic Mineral Products. Thus it is assumed that uncertainty of this “residual” activity data could be rather high especially for the last inventory year because the energy balance is based on preliminary data. Lime production data are presented in Table 109. Heavy metals emission factors are presented in the following subchapter. Fuel consumption and main pollutant emission factors are presented in Table 111.

Table 109: Lime production 1990 to 2018.

Year Lime [kt] Year Lime [kt] 1990 513 2004 786 1991 477 2005 788 1992 462 2006 781 1993 480 2007 816 1994 519 2008 846 1995 523 2009 695 1996 505 2010 765 1997 550 2011 810 1998 595 2012 761 1999 596 2013 779 2000 654 2014 787 2001 667 2015 772 2002 719 2016 773 2003 754 2017 775

- - 2018 735

79 http://www.ktn.gv.at/302524_DE-HCB-Messberichte



Glass manufacturing industry (SNAP 030317)

This category includes emissions from glass melting furnaces. Fuel consumption 1990 to 1994 is taken from (WIFO 1996). For the years 1997 and 2002 fuel consumption, SO2 and NOx emis-sions and for 2017 NOx emissions are reported from the Austrian association of glass manufactur-ing industry to the Umweltbundesamt GmbH by personal communication. Activity data for the years in between are interpolated. Natural gas consumption 2003 to 2004 is estimated by means of glass production data and an energy intensity rate of 7.1 GJ/t glass. Fuel consumption from 2005 onwards is taken from ETS. NOx and SO2 emissions for missing years of the time se-ries are calculated by implied emission factors derived from years were complete data is availa-ble. SO2 emissions include process emissions. For 2003 to 2016 NOX implied emission factors have been interpolated.

Fuel consumption and main pollutant emission factors are presented in Table 111. Table 110 shows the sum of flat and packaging glass production data. The share of flat glass in total glass production is about 5%.

Table 110: Glass production 1990 to 2017.

Year Glass [kt] Year Glass [kt]

1990 399 2004 357

1991 459 2005 418

1992 406 2006 448

1993 406 2007 497

1994 435 2008 504

1995 435 2009 443

1996 435 2010 498

1997 406 2011 474

1998 406 2012 472

1999 445 2013 487

2000 375 2014 497

2001 441 2015 497

2002 389 2016 481

2003 477 2017 502

- - 2018 487

Bricks and tiles manufacturing industry (SNAP 030319)

This category includes emissions from fuel combustion in bricks and tiles manufacturing industry. Bricks are baked with continuously operated natural gas or fuel oil fired tunnel kilns at tempera-tures around 1000°C. The chlorine content of porousing material is limited by a national regula-tion (HÜBNER 2001b). Activity data 1990 to 1995 is communicated by the Austrian association of non-metallic mineral industry. Activity data 1996 to 2004 are linearly extrapolated 1995 activity data. Activity data 2005 to 2018 is taken from ETS. For main pollutants default emissions fac-tors of industry are selected except for natural gas combustion for which the NOx emission fac-tor (294 kg/TJ) is taken from (WINDSPERGER et al. 2003). Table 111 presents fuel consumption and main pollutant emission factors.



1.A.2.f Fuel consumption and main pollutant emission factors

Table 111 shows activity data and main pollutant emission factors of 1.A.2.f sub categories ex-cept for SNAP 030311 cement industry were emission factors are not available by type of fuel. Underlined cells indicate emission factors other than default values for industrial boilers.

Table 111: NFR 1.A.2.f main pollutant emission factors and fuel consumption for the year 2018 by sub category.


Activity [TJ]

NOx [kg/TJ]

CO [kg/TJ]

NMVOC [kg/TJ]

SO2 [kg/TJ]

NH3 [kg/TJ]

SNAP 030312 Lime manufacturing Brown coal (BMWA 1990) (1) 281 170.0 150.0 23.0 630.0 0.02 Petrol coke (BMWA 1990) (1) 0 220.0 150.0 8.0 323.0(8) 0.01 Residual fuel oil < 1% S (BMWA 1996) (1) 0 235.0 15.0 8.0 398.0 2.70 Heating oil (BMWA 1996) (2) 1 65.0 15.0 4.8 0.5 2.70 Natural Gas (BMWA 1996) (1) 2 475 294.0(5) 30.0(6) 0.5 0.3(10) 1.00 Industrial waste (BMWA 1990) (1) 0 100.0 200.0 38.0 130.0 0.02 SNAP 030317 Glass manufacturing Residual fuel oil (BMWA 1996) (1) 4 299.1(11)

167.2(12)

15.0 8.0 442.9(7) 2.70 LPG (BMWA 1996) (3) 0 5.0 0.5 44.9(7) 1.00 Natural Gas (BMWA 1996) (1) 3 328 5.0 0.5 44.9(7) 1.00 SNAP 030319 Bricks and tiles manufacturing Brown coal (BMWA 1990) (1) 147 170.0 150.0 23.0 630.0 0.02 Coke oven coke (BMWA 1990) (1) 1 220.0 150.0 8.0 500.0 0.01 Petrol coke (BMWA 1990) (1) 61 220.0 150.0 8.0 323.0(8) 0.01 Residual fuel oil < 1% S (BMWA 1996) (1) 2 118.0 10.0 0.8 92.0 2.70 Residual fuel oil ≥ 1% S (BMWA 1996) (1) 79 235.0 15.0 8.0 398.0 2.70 Heating oil, Diesel oil (BMWA 1996) (2) 5 65.0 15.0 4.8 0.5 2.70 LPG (BMWA 1996) (3) 0 41.0 5.0 0.5 6.0(4) 1.00 Natural Gas (BMWA 1996) (1) 2 133 294.0(5) 5.0 0.5 0.3(10) 1.00 Industrial waste (BMWA 1990) (1) 50 100.0 200.0 38.0 130.0 0.02 Solid biomass (BMWA 1996) (1) 476 143.0 72.00 5.0 60.0 5.00 SNAP 030323 Magnesia Production Petrol coke (BMWA 1990) (1) 717 220.0 150.0 8.0 81.0(9) 0.01 Natural Gas (BMWA 1996) (1) 4 051 294.0(5) 5.0 0.5 0.3(10) 1.00 Industrial waste (BMWA 1990) (1) 27 100.0 200.0 38.0 130.0 0.02 Solid biomass (BMWA 1996) (1) 151 143.0 72.00 5.0 60.0 5.00

(1) Default emission factors for industry. (2) Default emission factors for district heating plants. (3) Values for natural gas are selected. (4) From (LEUTGÖB et al. 2003) (5) NOx emission factor of natural gas fired lime kilns and bricks and tiles production is taken from (WINDSPERGER et al.

2003). (6) CO emission factor of natural gas fired lime kilns is assumed to be 5 times higher than for industrial boilers. (7) SO2 emission factors of fuels used for glass manufacturing include emissions from product processing. (8) For petrol coke a sulphur content of 0.5% is assumed. The emission factor is calculated by means of the heating

value (emission factor SO2(g/GJ) = 2*0.5%*106/31GJ/t) (9) Same assumptions as for SNAPs 030312/030319 but 75% of sulphur remains in the product. (carbide). (10) EMEP 2016 Guidebook 1.A.4.b.i – table 3-13. (11) Implied emission factor 2002. (12) Implied emission factor 2018.



3.1.4.8 NFR 1.A.2.g.viii Other Stationary Combustion in Manufacturing Industries and Construction

Category 1.A.2.g.viii includes emissions of industrial boilers not considered in categories 1.A.2.a to 1.A.2.f. Table 112 presents the industrial branches, which are considered in category 1.A.2.g.viii

Table 112: ISIC divisions considered in category 1.A.2.g.viii

ISIC Division(s) Name 13 and 14 Mining and Quarrying (Non fuel) 17, 18 and 19 Textile and Leather 20 Wood and Wood Products 25 Rubber and Plastic Products 28, 29, 30, 32 and 33 Machinery and Instruments 34 and 35 Transport Equipment 36 Furniture 37 Recycling 45 Construction

The following Table 113 presents the fuel consumption of category 1.A.2.g.viii by type of fuel.

Table 113: Fuel consumption from NFR 1.A.2.g.viii Other Stationary Combustion in Manufacturing Industries and Construction 1990–2018.

NFR 1.A.2.g.viii 1.A.2.g.viii 1.A.2.g.viii 1.A.2.g.viii 1.A.2.g.viii 1.A.2.g.viii Fuel (PJ) liquid solid gaseous biomass other

1990 30.82 8.20 0.88 18.30 3.39 0.05 1991 33.06 8.95 0.84 19.16 3.52 0.58 1992 34.04 6.96 0.35 22.92 3.09 0.71 1993 34.36 10.65 0.64 19.59 2.96 0.52 1994 35.88 8.72 0.34 23.39 2.74 0.68 1995 39.32 10.55 0.17 25.68 2.24 0.67 1996 41.84 12.96 0.23 24.39 3.51 0.74 1997 41.07 18.44 0.49 16.91 3.77 1.46 1998 36.38 15.28 0.42 16.72 2.53 1.44 1999 35.29 8.26 1.17 15.88 9.10 0.87 2000 36.46 8.15 0.29 19.32 8.26 0.44 2001 35.66 9.12 0.07 17.29 8.38 0.80 2002 32.98 6.90 0.13 17.16 8.21 0.58 2003 37.32 8.66 0.12 18.19 9.64 0.72 2004 38.55 8.86 0.13 18.37 10.07 1.11 2005 52.40 9.41 0.33 23.65 17.48 1.52 2006 54.39 9.63 0.38 23.53 19.30 1.55 2007 57.13 7.81 0.30 23.07 24.32 1.62 2008 54.30 6.69 0.31 24.24 21.72 1.34 2009 57.33 6.73 0.00 25.72 23.69 1.20 2010 60.29 6.86 - 27.93 23.64 1.85



NFR 1.A.2.g.viii 1.A.2.g.viii 1.A.2.g.viii 1.A.2.g.viii 1.A.2.g.viii 1.A.2.g.viii Fuel (PJ) liquid solid gaseous biomass other

2011 58.80 7.05 - 24.38 24.45 2.92 2012 62.41 7.79 - 25.14 27.50 1.97 2013 60.84 4.08 0.01 28.56 25.90 2.30 2014 54.50 3.62 0.00 24.96 24.90 1.02 2015 50.76 3.43 0.00 23.08 23.81 0.43 2016 50.79 3.43 0.00 24.30 22.21 0.85 2017 50.65 3.05 0.02 25.08 21.68 0.82 2018 49.89 2.01 0.00 26.73 20.34 0.80 Trend 1990–2018 61.9% -75.4% -99.9% 46.1% 499.4% 1645.4% Trend 2017–2018 -1.5% -34.0% -96.2% 6.6% -6.1% -2.4%

Other manufacturing industry – boilers (SNAP 0301)

This sub category includes emissions of industrial boilers not considered in categories 1.A.2.a to 1.A.2.f. No specific distinction of technologies is made but national default emission factors of industrial boilers (BMWA 1990) are taken for emission calculation. It is assumed that facilities are not equipped with secondary emission controls. Activity data is taken from the energy balance.

Activity data and main pollutant emission factors are shown in Table 111.

Table 114 shows activity data and main pollutant emission factors of category 1.A.2.g.viii.

Table 114: NFR 1.A.2.g.viii main pollutant default emission factors and fuel consumption for the year 2018.


Activity [TJ]

NOx [kg/TJ]

CO [kg/TJ]

NMVOC [kg/TJ]

SO2 [kg/TJ]

NH3 [kg/TJ]

SNAP 0301 Other boilers Coke oven coke (BMWA 1990)(1) 1 220.0 150.0 8.0 500.0 0.01 Residual fuel oil < 1% S (BMWA 1996)(1) 681 118.0 10.0 0.8 92.0 2.70 Residual fuel oil ≥ 1% S (BMWA 1996)(1) 170 235.0 15.0 8.0 398.0 2.70 Heating oil, Diesel oil (BMWA 1996)(2) 215 65.0 15.0 4.8 0.5 2.70 LPG (BMWA 1996)(3) 949 41.0 5.0 0.5 6.0(4) 1.00 Natural gas (BMWA 1996)(1) 26 727 41.0 5.0 0.5 0.3(7) 1.00 Industrial waste (BMWA 1990)(1) 803 100.0 200.0 0.54 11.0 0.02 Fuel wood (BMWA 1996)(6) 11 110.0 370.0 5.00 11.0 5.00 Solid biomass (BMWA 1996)(1) 19 988 143.0 72.00 5.0 60.0 5.00 Sewage sludge (BMWA 1996)(1) 178 100.0 200.0 38.00 NA 0.02 Biogas (BMWA 1990)(5) 167 150.0 4.0 0.5 NA 1.00

(1) Default emission factors for industry. (2) Default emission factors for district heating plants. (3) Values for natural gas are selected. (4) From (LEUTGÖB et al. 2003) (5) Uncontrolled default emission factors for natural gas fired industrial boilers are selected. (6) Emission factors of wood chips fired district heating boilers are selected. (7) EMEP 2016 Guidebook 1.A.4.b.i – table 3-13.



3.1.4.9 Wood processing and chipboard manufacturing industries

For “wood and wood products” industry a branch specific set of emission factors has been ap-plied. A national study (WINDSPERGER 2018) carried out in 2018 provides new NOX and PM emission factors for biomass combustion of large chipboard production facilities and saw mills. The study is based on a survey conducted by the Austrian association of wood processing in-dustries (Fachverband der Holzverarbeitenden Industrie) for the year 2016. Emission factors have been derived from measurements and applied to total biomass consumption as provided in the Austrian energy balance.

Table 115: Wood processing and chipboard manufacturing emission factors and fuel consumption for the year 2018.

Fuel Activity [TJ] NOx [kg/TJ]

TSP [kg/TJ]

PM10 [kg/TJ] PM2.5 [kg/TJ]

Solid biomass 18 932 169.0(1) 133.0(2)

55.0(3)

7.6(4) 50.0

6.8 41.0

5.7 (1) NOX emission factor 1990 to 2000 (2) NOX emission factor 2016 (3) TSP emission factor 1990 to 1999 (4)TSP emission factor 2016


For cement industries (SNAP 030311) emission values were taken from (HACKL & MAUSCHITZ, 2001 to HACKL & MAUSCHITZ, 2019); in the Tables presented below implied emission factors (IEF) are given.

For the other sub categories emission factors were applied, references are provided below.

Coal

Emission factors for 1995 were taken from (CORINAIR 1997), Chapter B112, Table 12. For 1990 the emission factors were assumed to be 50% and for 1985 100% higher, respectively.

Fuel Oil

For fuel oil the same emission factors as for 1.A.1 were used.

Other Fuels

For fuel wood and wood wastes the value from (OBERNBERGER 1995) for plants > 4 MW was used for 1990. For fuel wood from 1995 onwards the value taken from personal information about emission factors for wood waste from the author was used.

For wood wastes from 1995 onwards the value for fuel wood of category 1.A.4.a (7 mg/GJ for Cd, 2 mg/GJ for Hg and 50 mg/GJ for Pb, valid for small plants) and a value of 0.8 mg/GJ for Cd, 13 mg/GJ for Hg and 1.0 mg/GJ for Pb, respectively, which are valid for plants with higher capacity (measurements at Austrian fluid bed combustion plants by FTU in 1999/2000) was weighted according to the share of overall installed capacity of the Austrian industry (25% high capacity and 75% low [< 5 MW] capacity).



Table 116: Cd emission factors for NFR 1.A.2 Manufacturing Industries and Construction.

Cadmium EF [mg/GJ] 1990 1995 2018 Coal 102A Hard coal 107A Coke oven coke

0.15 0.10 0.10

105A Brown coal 106A brown coal briquettes

0.60 0.40 0.40

Oil 204A Heating and other gas oil 2050 Diesel

0.02 (all years)

203B light fuel oil 0.05 (all years) 203C medium fuel oil 0.50 (all years) 203D heavy fuel oil 0.75 0.50 0.50 110A petrol coke 0.1 (all years) Other Fuels 111A Fuel wood 215A Black liquor

6.10 2.50 2.50

116A Wood waste 115A Industrial waste

6.10 2.35 2.35

Table 117: Hg emission factors for NFR 1.A.2 Manufacturing Industries and Construction.

Mercury EF [mg/GJ] 1990 1995 2018 Coal 102A Hard coal 107A Coke oven coke

2.55 1.70 1.70


6.60 4.40 4.40

Oil 204A Heating and other gas oil 2050 Diesel

0.007 (all years)

203B light fuel oil 0.015 (all years) 203C medium fuel oil 0.04 (all years) 203D heavy fuel oil 0.75 (all years) 110A petrol coke 1.70 (all years) Other Fuels 111A Fuel wood 215A Black liquor 116A Wood waste 115A Industrial waste

1.90 1.25 1.25

Table 118: Pb emission factors for NFR 1.A.2 Manufacturing Industries and Construction.

LEAD EF [mg/GJ] 1990 1995 2018 Coal 102A Hard coal 107A Coke oven coke

9.00 6.00 6.00


5.85 3.90 3.90

Oil 204A Heating and other gas oil 0.02 (all years)



LEAD EF [mg/GJ] 1990 1995 2018 2050 Diesel 203B light fuel oil 0.05 (all years) 203C medium fuel oil 1.20 (all years) 203D heavy fuel oil 0.19 0.13 0.13 110A petrol coke 6.00 (all years) Other Fuels 111A Fuel wood 215A Black liquor 116A Wood waste

26.3 21.15 21.15

115A Industrial waste 72.00 (all years)

Emission factors not related to fuel input

The following Tables show production data of iron and steel, non-ferrous metals and other activity data for selected years used as activity data for calculating heavy metals and POPs emissions from products processing.

Table 119: Non-ferrous metals production [t].

Year Nickel Production (SNAP 030324)

[t]

1990 638

1995 822

2000 2 000

2010 2 000

2018 2 000

Nickel Production is taken from (ÖSTAT INDUSTRIE- UND GEWERBESTATISTIK), (EUROPEAN COMMISSION IPPC BUREAU 2000) and the nickel-institute (www.nickelinstitute.org). Table 120: Activity data for calculation of HM and POP emissions with EF not related to fuel input.

Year Cast Iron Production [kt] Cement clinker [kt]

1990 110 3 694

1991 101 3 635

1992 83 3 820

1993 65 3 678

1994 68 3 791

1995 69 2 930

1996 65 2 916

1997 66 3 103

1998 74 2 869

1999 71 2 892

2000 75 3 053

2001 75 3 061

2002 71 3 118

http://www.nickelinstitute.org/



Year Cast Iron Production [kt] Cement clinker [kt]

2003 69 3 120

2004 76 3 223

2005 76 3 221

2006 81 3 653

2007 87 3 992

2008 87 3 996

2009 54 3 428

2010 65 3 097

2011 67 3 176

2012 63 3 206

2013 67 3 156

2014 65 3 143

2015 61 3 257

2016 56 3 300

2017 61 3 313

2018 64 3 552

Table 121: Asphalt concrete production 1990 and 2018.

Year Asphalt concrete [kt]

1990 403

2018 522

Emission factors for Iron and Steel: reheating furnaces were taken from (WINIWARTER & SCHNEIDER 1995).

For lime production the emission factors for cement production (HACKL & MAUSCHITZ 2001) were used, as the two processes are technologically comparable.

Pb and Cd emission factors for glass production base on measurements at two Austrian facilities for the year 2000. As emission limits are legally restricted, and for 1995 the emission allowanc-es were higher, for 1995 twice the value of 2000 was used. For 1990 and 1985 the Cd and Pb emission factors as well as the Hg emission factor are from (WINIWARTER & SCHNEIDER 1995).

Heavy metals emissions from burning of fine ceramic materials arise if metal oxides are used as pigments for glaze. The emission factors for fine ceramic materials base on results from (BOOS 2001), assuming that HM concentrations in waste gas is 5% of raw gas concentrations.

Emission factors for nickel production base on measurements at the only relevant Austrian facility.



Table 122: HM emission factors not related to fuel input for NFR 1.A.2 Manufacturing Industries and Construction.

NFR SNAP Category Description EF [mg/t Product]

Cd Hg Pb

1.A.2.a 030302 Iron and Steel: reheating furnaces

50 – 2 400

1.A.2.f 030311 Cement production

(year 2017 value)

1.91 39.7 9.82

1.A.2.f 030312 Lime production 8.7 21 29

1.A.2.f 030317 Other glass 150–880 50–3084 12 000–20084

1.A.2.f 030320 Fine ceramic materials 150 – 5 000

1.A.2.b 030324 Nickel production 5 570 230


For cement industries the dioxin (PCDD/F) emission factor of 0.01 µg/GJ is derived from meas-ured 0.02 ng TE/Nm³ at 10% O2 (WURST & HÜBNER 1997) assuming a flue gas volume of 1 600–1 700 Nm³/t cement clinker (HÜBNER 2001b) and an average energy demand of 3.55 GJ/t ce-ment clinker. HCB emission factors are taken from (HÜBNER 2001b). The PAK4 emission factor of 0.28 mg/GJ fuel input is derived on actual measurements communicated to the Umweltbun-desamt.

The dioxin (PCDD/F) emission factor for bricks and tiles and lime production is based on find-ings of the study (WURST & HÜBNER 1997). HCB emissions were calculated on the basis of diox-in emissions and assuming a factor of 200.

For pulp and paper industries the dioxin emission factor of 0.009 µgTE/GJ for all fuels bases on measurements of fluidized bed combustors in pulp and paper industries (Wurst, F. & C.Hübner 1997) and data from literature with typical fuel mixes (LAI-REPORT 1995), (NUSSBAUMER 1994). HCB emissions were calculated on the basis of dioxin emissions and assuming a factor of 200.

For the other sub categories emission factors for plants with different capacities were applied, together with assumptions on plant structure of the Austrian industry mean values for each fuel were calculated. The IEFs (average EF per fuel category) were used for all years; they are pre-sented in Table 124.

Emission factors for dioxin were taken from (WURST & HÜBNER 1997) and measurements at Austrian plants (FTU 2000).

References for PAK emission factors are provided in the following table.

80 upper value for 1985, lower value for 2000; years in between were linearly interpolated



Table 123: Source of PAH emission factor of different fuels.

PAH4 EF [mg/GJ]

Small plants ≤ 0.35 MW

Medium plants 0.35–1 MW

Large plants 1–50 MW

Source of selected emission factors

Natural gas

0.04 NA NA For households, central heating (HÜBNER 2001b); for larger plants not relevant

Heating oil

0.24 0.16 0.16 For small plants: households central heating (HÜBNER 2001b); for larger plants: (UBA BERLIN 1998) (four times the value of BaP).

Fuel oil 0.24 0.24 0.24 (UBA BERLIN 1998) (four times the value of BaP)

Wood 85 2.7 0.055 For small plants: households central heating (HÜBNER 2001b); for larger plants: measurements at Austrian plants by (FTU 2000).

Coal 85 2 0.04 For small plants: households central heating (HÜBNER 2001b); for large plants: (UBA BERLIN, 1998) (four times the value of BaP). For medium plants: expert judgement81.

For other oil products the same emission factors as for category 1.A.1 were used.

For gaseous biofuels the same emission factors as for gas were used.

PCB emission factors have been selected as outlined in chapter 3.1.3.

Table 124: POP emission factors (average EF per fuel category) for 1.A.2 Manufacturing Industries and Construction.

PCDD/F [µg/GJ]

HCB [µg/GJ]

PAK4 [mg/GJ]

PCB [µg/GJ]

All fuels in pulp and paper ind.

Solid biomass in pulp and paper ind.

0.009 1.8 0.055 -

0.0008

Coal

Hard coal 0.042 4.5 2.0 170

Brown coal 0.033 3.6 2.0 170

Brown coal briquettes 0.064 6.6 2.0 170

Coke oven coke 0.052 5.5 2.0 170

Fuel Oil

Fuel Oil 0.0009 0.12 0.24 85

Heating and other gas oil 0.0006 0.095 0.18 NA

Other Oil Products 0.0017 0.14 0.011 NA

Gas

Natural gas 0.0006 0.072 0.0032 (for iron and steel)

0.055 (for pulp and paper)

NA (other sub categories)

NA

LPG 0.0006 0.079 0.004 NA

81 As the size structure for coal fired plants was not known, the EF for medium plants – which is the main size – was

used for all activity data in this category.



PCDD/F [µg/GJ]

HCB [µg/GJ]

PAK4 [mg/GJ]

PCB [µg/GJ]

Other Fuels

Fuel Wood 0.083 13.0 2.7 0.0075

Industrial waste Wood Waste

0.083 13.0 3.3 0.0075

Gaseous biofuels 0.0006 0.072 0.0032 NA

Emission factors not related to fuel input

Dioxin emission factors for reheating furnaces in iron and steel industries (foundries) were taken from (UBA BERLIN 1998) (average of hot air and cold air furnaces).

For calculation of PAK emissions from reheating furnaces in iron and steel industries the same emission factor as for coke in blast furnaces was used, as the coke fired reheating furnaces are technologically comparable to these.

HCB emissions for foundries were calculated on the basis of dioxin emissions and assuming a factor of 200.

POPs emissions are released in asphalt concrete plants when the bitumen/flint mixture is heat-ed.

As dioxin EF the mean value of the emission factors given in (US-EPA 1998) was applied.

The PAK emission factor for asphalt concrete plants was taken from (SCHEIDL 1996).

Nickel is mainly produced by one company which uses catalysts and other potential recyclable as raw material. The raw material is processed in a rotary kiln and an electric arc furnace. Diox-in emissions 1993 are taken from an emissions declaration. Dioxin emissions of the remaining time series are calculated by multiplying production data with the implied emission factor of 1993.

The dioxin emission factor for nickel production bases on measurements in the only relevant Austrian facility.

Table 125: POP emission factors not related to fuel input for Sector 1.A.2 Manufacturing Industries and Construction.

Dioxin [µg/t]

HCB [µg/t]

PAK4 [mg/t]

030302 Iron and Steel: reheating furnaces 0.25 50 1.1

030311 Cement production (2017 value) 0.039 5.83 1.09

030313 Asphalt concrete plants 0.014 2.8 0.15

030324 Nickel production 13 2 600–2.2582 –

82 Higher value for 1995/1990, lower value for 2000




As already described in Chapter 1.4 the emission inventories of PM for different years were prepared by contractors and incorporated into the inventory system afterwards.

The emission factors were taken from (WINIWARTER et al. 2001) and were used for the whole time series except for cement production (NFR 1.A.2.f): emissions taken from (HACKL & MAUSCHITZ 1995/1997/

2001/2003/2007-2011) are included in category 2.A.1. NFR 1.A.2.d pulp, paper and print: emission values until 2017 were taken from (AUSTROPAPIER

2002–2018) and default national emission factors for industrial boilers have been adapted to fit the emissions. From the year 2018 onwards, emissions factors from (IIÖ 2019) have been applied for the most relevant fuels (coal, black liqueur, solid biomass and natural gas).

For these sources IEFs are presented in the following Table. The shares of PM10 and PM2.5 were taken from (WINIWARTER et al. 2001).

Table 126: PM emission factors for NFR 1.A.2.

TSP Emission Factors [g/GJ] PM10 PM2.5 1990 1995 2000 2018 [%] [%]

Gas

Natural gas & LPG 0.5 90 75

Natural gas – Pulp & Paper (IEF) 0.20 0.10 0.11 0.78 90 75

Coal

Hard coal & Coke oven coke 45 90 75

Brown coal & Brown coal briquettes

50 90 75

Coal – Pulp & Paper industries (IEF)

7.94 3.92 4.46 8.20 95 80

Oil

Light fuel oil & Gasoil 3.0 90 75

Medium fuel oil 35 90 75

Heavy fuel oil 65 90 75

Other kerosene 3.0 95 80

Oil – Pulp & Paper industries (IEF) 19.85 9.81 11.16 7.64 90 75

Other Fuels

Fuel wood, Wood waste & Industrial waste

55 90 75

Fuel wood, Wood waste & Industrial waste – Pulp & Paper (IEF)

13.65 4.91 5.58 1.50 90 75

Black liquor – Pulp & Paper industries (IEF)

40.94 14.72 11.16 5.60 90 75

Gaseous biofuels 0.5 90 75


Updates of activity data and of NCVs follow the updates of the IEA-compliant energy balance compiled by the federal statistics authority Statistik Austria (Chapter 3.1.9).



The most significant recalculations for the year 2017 took place for categories:

1.A.2.d: -0.8 kt NOx

1.A.2.c: -0.2 kt SO2, -0.14 kt PM2.5

1.A.2.e: -0.3 kt NOx, -0.05 kt PM2.5

Non-ferrous metals (1A2b)

Activity data of secondary nickel production have been updated. SO2, Cd and Hg emissions from nickel production are now plant specific and SO2 emission are reported the first time.

Pulp and paper industry (1A2d)

Based on a new study performed in 2019, NOx and PM2.5 emission factors from hard coal, black liqueur and wood waste used in pulp and paper industries have been revised, resulting in about -0.8 kt lower NOx and slightly higher PM2.5 emissions 2017.

Chemicals industry (1A2c)

NOx, SO2 and PM10 emissions from a large waste incineration plant are now taken from meas-ured data. This results in about -0.1 kt lower NOx, -0.3 kt lower SO2 and -0.2 kt lower PM2.5 emissions from category 1A2c in the year 2017.

3.1.5 NFR 1.A.3.e.1 Pipeline compressors

Category 1.A.3.e considers emissions from natural gas powered turbines used for natural gas pipelines transport. The simple CORINAIR methodology is used for emissions calculation except for NOx emissions, which are based on reported data.

Activity data is taken from the energy balance. The following Table 127 shows activity data and main pollutant emission factors. The NOx emission factor of 150 kg/TJ is an expert guess by Umweltbundesamt. Since 2007 the NOx emissions as reported in emissions declarations (http://www.edm.gv.at) have been used for the inventory.

Heavy metal and PAK4 emission factors are from the EMEP Guidebook 2016 table 3-17. The PCB emission factor is derived from the PCCD/F factor (see Table 89)

Table 127: NFR 1.A.3 e main pollutant emission factors and fuel consumption for the year 2018.


Activity [TJ]

NOx [kg/TJ]

CO [kg/TJ]

NMVOC [kg/TJ]

SO2 [kg/TJ]

NH3 [kg/TJ]

Natural Gas (BMWA 1996) (1) 10 870 150.0(2)

33.0(3)

5.0 0.5 0.3 1.00

Cd [mg/GJ]

Hg [mg/GJ]

Pb [mg/GJ]

PAK4 [mg/GJ]

PCB [µg/GJ]

0.0003 0.1 0.0015 0.0116 0.000018

(1) Default emission factors for industry. (2) Emission factor 1990 to 2006. (3) Implied emission factor 2018.

http://www.edm.gv.at/



3.1.6 Quality Assurance and Quality Control (QA/QC)

Comparison with EPER and E-PRTR data

Comparison of emissions with reported 2004/2005 EPER and 2007–2015 E-PRTR data does not explicitly identify inconsistencies for main pollutants.

1.A.1.a Activity data and GHG emissions are in general of high quality due to the needs of GHG calcu-lation and CO2-trading. The quality system which is well defined for GHG is basically also ap-plied to non-GHG but is not always fully documented in the inventory system. The following QA/QC procedures are performed depending on resource availability.

Since inventory year 2007 large combustion plant data is reported via the online EDM (electron-ic data management, module “eVerbrennung”) system.

1.A.1.a LPS data gap filling (DKDB)

It has to be noted that emissions from DKDB (“Dampfkessel-Datenbank”) had been reported for heating periods from October year(n) to September year(n+1) for the years 1990 to 2006. Due to this circumstance and in case of other missing values emissions and fuel consumption for an inventory year data was completed by taking the monthly values from the previous inventory year if available. In some cases either activity data or emission data was not complete and gap filling has been performed by using other monthly emission ratios of that plant. For boilers with mixed fuel consumption a linear regression model was sometimes used.

1.A.1.a LPS data validation (DKDB)

An outcome of the methodology as presented in Table 75 is the ratios of measured and calculat-ed emissions by fuel type. Possible reasons for unexplainable ratios: Default emission factors are not appropriate because the group includes inhomogeneous

boiler technologies. Changed technologies are not reflected. Boilers used for default emission factor derivation are not the consistent with boilers consid-

ered in the inventory approach. Emission declarations are not appropriate (fuel consumption is not consistent with emissions). Activity data of large boilers and other large plants is checked with the national energy balance. For some fuels (coal, residual fuel oil, waste) and categories total national consumption is lim-ited to a few boilers. In this case LPS consumption may be checked with data from Statistik Austria or with the spatial „Bundesländer” energy balance. In some cases published environ-mental reports which are underlying a QA/QC system like EMAS have been used for validation purpose.

1.A.1.b Petroleum refining

Reported fuel consumption is checked with energy balance. Monthly data from DKDB provides emissions by boiler which is cross-checked with reported flue gas concentrations or mandatory limits.



3.1.7 Planned improvements

Currently no specific improvements are planned.

3.1.8 Recalculations

This chapter presents the recalculation based on revised fuel combustion activity data ex-pressed as the difference to the previous submission.

Revision of the energy balance

Federal statistics office “Statistik Austria” revised the energy balance for the years 1990 to 2017 with the following main implications for energy consumption as used in the inventory: Natural gas gross inland consumption 2014 and 2015 has been revised by -1 to -1.8 TJ.

However, natural gas consumption has been shifted between sectors: For 2005 and 2006, about 1 to 1.2 PJ have been shifted from the power sector (1A1a) to the commercial sector (1A4a). For 2011, about 0.7 PJ have been shifted from the power sector (1A1a) to the com-mercial sector (1A4a). For 2013, about 1.7 PJ have been shifted from the commercial and residential sector (1A4a and 1A4b) to the industry sector (1A2). For 2014, about 1.1 PJ have been shifted from the residential and commercial sector (1A4a and 1A4b) to the industrial sector (1A2). For 2016, about 3 PJ have been shifted from petroleum refineries (1A1b) to the residential and industry sector (1A4b, 1A2).

For liquid fuels, gross inland consumption has been revised between -0.1 to -2.2 PJ for the years 2005 to 2011 (crude oil input into refineries) and by -1.3 PJ PJ for the year 2017, which does not have an effect on final consumption, because lower fuel imports have been coun-terbalanced by a higher refinery fuel output. For 2013 to 2017, between 1.1 to 4.6 PJ of liquid fuels have been shifted from the industry sector (mostly from 1A2e food processing and 1A2g other manufacturing industries) to the residential (1A4b) and commercial (1A4a) sector.

For solid fuels, mainly the residential sector has been revised since the year 2005 (+ 1 PJ in 2005 and + 0.2 PJ in 2017).

For ‘biomass’, gross inland consumption has been revised upwards for the whole time series since 2005 – 2017 (2005: + 7 PJ, 2010: +15.7 PJ, 2015: 9.4 PJ, 2017: +14.5 PJ). For the years 2005 to 2016 the transformation input to the power sector (1A1a) has been revised downwards (between -0.4 to -2.7 PJ) while for 2017 it has been revised upwards by +3.5 PJ which explains most of the higher NOX (+7%) and PM2.5 (+6%) emissions 2017 of category 1A1a. The highest revision of biomass consumption took place in the 1A4 stationary combus-tion sub categories, with increases of +6.4 PJ in 2005 and + 12.6 PJ in 2017.



3.1.9 NFR 1.A.4 Other sectors

Category 1.A.4 Other sectors enfolds emissions from stationary fuel combustion in the small combustion sector. It also includes emissions from mobile sources in households and gardening including snow cats and skidoos as well as from agriculture and forestry.

Source Description

Category 1.A.4 Oher Sectors includes emissions from stationary fuel combustion in the small combustion sector as well as from some mobile machinery. Emissions of public district heating plants are included in category 1.A.1.a Public Electricity and Heat Production. Emissions of dis-trict heat generation delivered to third parties by industry are included in 1.A.2 Manufacturing Industries and Construction. Information about type of heating is derived from an energy de-mand model for space heating based on heating market surveys validated by micro census sur-veys and calibrated according to the energy statistics supplier. A clear distinction between “real” public district heating or micro heating networks which serve several buildings under same ownership cannot always be made by the interviewed person or interviewers.

Table 128 presents non-combustion PM emission sources.

Table 128: PM2.5 emissions from non-combustion sources in 2018.

Source NFR PM2.5 [t] Bonfire 1.A.4.a.i 150 Open fire pits 1.A.4.a.i 16 Barbecue 1.A.4.b.i 763 Total 929

Table 129 shows NFR 1.A.4 category definitions partly taken from the IPCC 2006 Guidelines.

Table 129: NFR 1.A.4 category definitions.

Code Number and Name Definitions 1.A.4 OTHER SECTORS Combustion activities as described below, including combustion for

the generation of electricity and heat for own use in these sectors.

1.A.4 a Commercial/Institutional Fuel combustion in commercial and institutional buildings; all activities included in ISIC Divisions 41, 50, 51, 52, 55, 63–67, 70–75, 80, 85, 90–93.And 99. Bonfire and open fire pits.

1.A.4 b Residential Fuel combustion in households.

1.A.4 b 1 Residential: stationary Fuel combustion in buildings. Barbecue.

1.A.4 b 2 Residential: Household and gardening (mobile) 83

Fuel combusted in non-commercial mobile machinery such as for gardening and other off road vehicles.

1.A.4 c Agriculture/Forestry/Fishing Fuel combustion in agriculture, forestry, fishing and fishing industries such as fish farms. Activities included in ISIC Divisions 01, 02.And 05. Highway agricultural transportation is excluded.

83 methodologies for mobile sources are described in Chapter 3.2.7.1



Code Number and Name Definitions 1.A.4 c 1 Stationary Fuels combusted in pumps, grain drying, horticultural

greenhouses and other agriculture, forestry or stationary combustion in the fishing industry.

1.A.4 c 2 Off-road Vehicles and Other Machinery 83

Fuels combusted in traction vehicles and other mobile machinery on farm land and in forests.

1.A.4 c 3 National Fishing 83 Fuels combusted for inland, coastal and deep-sea fishing. Fishing should cover vessels of all flags that have refuelled in the country (include international fishing).

3.1.9.1 Methodology

A country specific tier 2 methodology is applied.

Twenty-two technology and fuel dependent main sub categories (heating types) are considered in this category as presented in the following table:

Table 130: Heating types of category 1.A.4. Other sectors – stationary sources.

No. Heating type Fuel

#1 Fuel oil boilers Light fuel oil, medium fuel oil, heavy fuel oil, diesel, petroleum, other petroleum products

#2 Gas oil stoves Gas oil

#3 Vapourizing burners Gas oil

#4 Yellow burners Gas oil

#5 Blue burners with conventional technology

Gas oil

#6 Blue burners with low temperature or condensing technology

Gas oil

#7 Natural gas convectors Natural gas

#8 Atmospheric burners Natural gas, sewage sludge gas, biogas and landfill gas

#9 Forced-draft natural gas burners Natural gas, sewage sludge gas, biogas and landfill gas

#10 LPG stoves LPG and gas works gas

#11 LPG boilers LPG and gas works gas

#12 Wood stoves and cooking stoves Fuel wood

#13 Tiled wood stoves and masonry heaters

Fuel wood

#14 Mixed-fuel wood boilers Fuel wood

#15 Natural-draft wood boilers Fuel wood

#16 Forced-draft wood boilers Fuel wood

#17 Wood chips boilers with conventional technology

Wood waste

#18 Wood chips boilers with oxygen sensor emission control

Wood waste

#19 Pellet stoves Wood waste

#20 Pellet boilers Wood waste

#21 Coal stoves Hard coal and Hard coal briquettes, lignite and brown coal, brown coal briquettes, coke, peat

#22 Coal boilers Hard coal and Hard coal briquettes, lignite and brown coal, brown coal briquettes, coke, peat, industrial waste



In addition, the whole fuel consumption of char coal is assumed to be combusted in devices similar to wood stoves and cooking stoves and calculated separately.

For each technology fuel dependent emission factors are applied.

Activity data

Total fuel consumption for each of the sub categories of 1.A.4 is taken from the national energy balance. From the view of energy statistics compilers this sector is sometimes the residual of gross inland fuel consumption because fuel consumption data of energy industries and manufacturing industry is collected each year in more detail and therefore of higher quality. However, in case of the Austrian energy balance fuel consumption of the small combustion sector is modelled over time series in consideration of heating degree days, micro census data and service industries survey panel.

Information about type of heating is derived from an energy demand model for space heating, which consists of five consecutive modules: Building and dwelling stock: by building type, year of construction, type of residence (number

of buildings and dwellings, net floor area, useful area, number of residents) (BMNT 2018, STATCUBE 2014a, 2014b, 2014c, 2019a,b STATISTIK AUSTRIA 1973, 1982, 1992a, 2004, 2013, 2018, 2019a)

Heating type by energy carrier: by categories of module ‘building and dwelling stock’ and en-ergy carrier including heat pumps, district heating, solar thermal and electric heating (number of buildings and dwellings, net floor area, useful area, number of residents) (STATISTIK AUSTRIA 2019b)

Heating type by technology: by categories of module ‘building and dwelling stock’, type of ap-plication (as main or auxiliary heating) and twenty-two technology and fuel dependent sub-categories (number of buildings and dwellings, net floor area, useful area, residents) (UMWELTBUNDESAMT 2014, E7 ENERGIE MARKT ANALYSE GMBH 2009, 2017)

Building energy performance: by categories of module ‘building and dwelling stock’ based on type of energy-efficient building renovation, year of construction and residents (space heating demand, hot water demand) (AEA 2015, BMWFW 2014)

Final energy demand by technology: by categories of module ‘heating type by technology’ based on results of module ‘building energy performance’ considering heating degree days (ZAMG 2019) and calibrated according to the energy statistics supplier to maintain consisten-cy with fuel demand reported in (IEA JQ 2019)

Activity data by type of heating is selected as the following:

1.A.4.a.1 Commercial/Institutional: stationary

The fuel consumption reported in (IEA JQ 2019) is assigned to twenty-two heating types derived from an energy demand model for space heating based on heating market surveys and cali-brated according to the energy statistics supplier (see section Activity data above).



Table 131: Fuel consumption from NFR 1.A.4.a.1 Commercial/Institutional: Stationary 1990–2018.

NFR 1.A.4.a.1 1.A.4.a.1 1.A.4.a.1 1.A.4.a.1 1.A.4.a.1 1.A.4.a.1 Fuel (PJ) liquid solid gaseous biomass other

1990 35.55 18.66 0.96 12.75 2.06 1.11 1991 37.87 17.91 1.27 15.64 2.08 0.97 1992 46.05 18.29 0.92 24.22 1.93 0.69 1993 50.33 17.69 0.86 28.86 2.59 0.33 1994 41.71 15.57 0.80 22.32 2.50 0.51 1995 52.14 17.64 0.64 30.79 2.55 0.52 1996 52.14 23.72 0.67 24.80 2.40 0.55 1997 52.68 27.53 0.92 20.93 2.73 0.58 1998 50.15 24.73 0.74 21.37 2.71 0.61 1999 59.14 27.78 0.92 25.83 4.00 0.61 2000 49.00 17.84 1.10 25.24 4.26 0.56 2001 63.82 23.65 1.23 35.03 3.29 0.63 2002 60.91 24.92 0.86 31.38 3.13 0.62 2003 70.48 30.58 1.18 34.46 3.62 0.65 2004 69.86 23.40 0.83 40.83 4.27 0.52 2005 51.56 26.86 0.72 19.99 2.92 1.07 2006 54.60 28.67 0.52 21.02 3.66 0.72 2007 42.57 19.87 0.41 18.05 3.91 0.33 2008 45.53 20.92 0.25 19.95 4.35 0.05 2009 37.20 16.92 0.19 16.48 3.56 0.05 2010 30.55 9.49 0.22 16.65 4.13 0.06 2011 26.29 8.83 0.15 13.95 3.32 0.05 2012 24.48 5.99 0.00 15.85 2.64 NO 2013 24.09 5.87 0.01 15.52 2.62 0.07 2014 22.35 6.01 0.00 13.70 2.57 0.08 2015 23.97 5.95 0.00 14.74 3.19 0.08 2016 22.08 5.60 NO 13.72 2.67 0.09 2017 26.27 7.73 NO 14.54 3.92 0.08 2018 24.71 6.72 NO 14.38 3.51 0.09 Trend 1990–2018

-30.5% -64,0% -100,0% 12,8% 70,4% -91,5%

Trend 2016–2018

-5.9% -13,0% NO -1,0% -10,4% 13,1%



Table 132: Share of 1.A.4.a heating type on fuel category for the year 2018.

Fuel No. Heating type Share of heating type [% TJ]

1.A.4.a

Light fuel oil #1 Fuel oil boilers 100.0%

Medium fuel oil #1 Fuel oil boilers NO

Heavy fuel oil #1 Fuel oil boilers NO

Diesel #1 Fuel oil boilers 100.0%

Petroleum #1 Fuel oil boilers NO

Gas oil #2 #3 #4 #5

#6

Gas oil stoves Vaporizing burners Yellow burners Blue burners with conventional technology Blue burners with low temperature or condensing technology

4.9% 2.0%

42.8% 1.6%

48.8%

Natural gas #7 #8 #9

Natural gas convectors Atmospheric burners Forced-draft natural gas burners

18.9% 47.1% 33.9%

Biogas and landfill gas #8 #9

Atmospheric burners Forced-draft natural gas burners

58.1% 41.9%

LPG and gas works gas #10 #11

LPG stoves LPG boilers

66.9% 33.1%

Fuel wood #12 #13

#14 #15 #16

Wood stoves and cooking stoves Tiled wood stoves and masonry heaters Mixed-fuel wood boilers Natural-draft wood boilers Forced-draft wood boilers

4.1% 95.9%

NO NO NO

Wood waste #17

#18

#19 #20

Wood chips boilers with conventional technology Wood chips boilers with oxygen sensor emission control Pellet stoves Pellet boilers

3.8%

31.2%

5.0% 60.1%

Hard coal and hard coal briquettes

#21 #22

Coal stoves Coal boilers

NO NO

Lignite and brown coal #21 #22


NO NO

Brown coal briquettes #21 #22


NO NO

Coke #21 #22


NO NO

Peat #21 #22


NO NO

Industrial waste #22 Coal boilers 100.0%

Char coal BBQ Barbecue 100.0%

NO…not occurring (in 2018)



Table 133: NFR 1.A.4.a.1 percentual consumption by type of heating.

Fuel group Natural Gas Fuel Oil, LPG Gasoil

Heating type No. #7 #8 #9 #1 #10 #11 #2 #3 #4 #5 #6

Year [% TJ] [%TJ] [%TJ]

1990 29.9 57.0 13.1 91.5 7.5 0.9 11.8 1.5 77.2 1.7 7.8

1991 27.5 57.9 14.6 84.6 13.6 1.8 11.7 1.5 75.8 1.7 9.2

1992 25.7 57.9 16.3 74.9 22.1 3.0 11.6 1.4 73.9 2.1 11.0

1993 23.8 58.2 18.0 72.2 24.3 3.4 11.4 1.4 72.0 2.8 12.5

1994 22.3 57.7 20.1 71.4 24.9 3.7 11.2 1.3 69.5 3.7 14.2

1995 20.7 57.2 22.1 79.2 18.0 2.8 11.0 1.3 67.1 4.8 15.8

1996 19.1 56.7 24.2 89.0 9.5 1.5 10.9 1.2 63.6 6.2 18.1

1997 18.0 55.9 26.1 80.5 16.7 2.8 10.6 1.2 61.1 7.2 19.9

1998 16.9 55.1 28.0 78.8 18.0 3.2 10.4 1.1 58.0 8.3 22.2

1999 15.9 54.2 29.9 83.4 14.0 2.6 10.2 1.1 56.5 8.8 23.4

2000 15.1 53.4 31.5 82.8 14.5 2.8 9.9 1.1 55.6 9.1 24.3

2001 15.1 52.4 32.5 85.9 11.6 2.5 9.7 1.1 54.6 9.4 25.2

2002 15.4 51.2 33.4 75.5 19.8 4.7 9.3 1.1 53.9 9.7 26.1

2003 15.4 50.4 34.2 71.1 23.0 5.9 8.9 1.1 53.7 9.8 26.5

2004 15.7 49.4 34.8 49.8 39.2 11.0 8.5 1.1 52.8 10.0 27.6

2005 15.8 48.9 35.3 51.4 37.4 11.2 8.1 1.1 52.7 9.6 28.6

2007 16.1 48.2 35.7 68.2 24.1 7.7 7.7 1.2 52.6 9.1 29.4

2007 16.5 47.7 35.8 54.3 34.0 11.7 7.4 1.2 52.1 8.6 30.7

2008 16.7 47.3 36.0 42.0 42.6 15.4 7.1 1.3 51.6 8.0 32.0

2009 16.9 47.0 36.2 46.5 38.7 14.8 6.7 1.3 51.1 7.4 33.4

2010 16.8 46.9 36.4 7.4 66.2 26.4 6.4 1.4 50.5 6.7 35.0

2011 17.3 46.5 36.2 24.4 53.2 22.4 6.1 1.4 49.7 6.0 36.8

2012 17.5 46.4 36.1 71.1 20.1 8.8 5.8 1.5 48.9 5.2 38.6

2013 17.7 46.3 36.0 74.6 17.5 8.0 5.6 1.6 48.0 4.3 40.5

2014 18.3 46.1 35.6 82.4 11.9 5.7 5.3 1.7 47.1 3.4 42.6

2015 18.2 46.4 35.4 79.5 13.7 6.8 5.0 1.8 46.1 2.3 44.8

2016 18.0 46.8 35.2 90.2 6.6 3.3 5.0 1.9 45.0 1.7 46.5

2017 17.9 47.3 34.8 65.8 22.9 11.3 4.9 1.9 43.8 1.6 47.7

2018 18.0 47.7 34.3 48.7 34.4 17.0 4.9 2.0 42.8 1.6 48.8

NO…not occurring



Table 134: NFR 1.A.4.a.1 percentual consumption by type of heating (continued).

Fuel (group) Fuel Wood (log wood) Wood chips, pellets and other biomass

Coal (+ Briquettes)

Heating type No. #12 #13 #14 #15 #16 #17 #18 #19 #20 #21 #22*


1990 2.1 51.4 44.9 NO 1.6 89.3 10.7 NO NO 39.2 60.8

1991 1.9 51.5 44.4 NO 2.2 76.5 10.9 0.0 12.6 46.3 53.7

1992 2.0 51.2 43.9 NO 2.9 63.9 12.6 0.0 23.4 46.8 53.2

1993 2.0 51.2 43.4 NO 3.5 54.6 13.0 0.1 32.3 57.0 43.0

1994 2.1 50.8 42.9 NO 4.2 46.3 13.6 0.3 39.9 50.1 49.9

1995 1.9 50.7 42.6 NO 4.8 39.5 13.8 0.6 46.1 46.4 53.6

1996 1.7 50.5 42.3 NO 5.5 34.2 13.4 1.1 51.3 46.7 53.3

1997 1.9 49.8 42.0 NO 6.3 29.6 13.0 1.6 55.9 51.9 48.1

1998 2.0 49.1 41.9 NO 7.0 25.6 12.6 2.0 59.8 47.7 52.3

1999 2.0 48.4 41.8 NO 7.8 22.1 12.3 2.4 63.2 53.1 46.9

2000 2.2 47.4 41.8 NO 8.6 18.9 12.0 2.8 66.3 58.8 41.2

2001 2.1 51.2 38.2 NO 8.6 21.5 15.7 3.3 59.5 58.7 41.3

2002 2.2 54.4 34.8 0.0 8.5 21.8 18.2 3.5 56.5 52.2 47.8

2003 2.1 57.9 31.5 0.1 8.3 21.4 20.3 3.6 54.8 57.2 42.8

2004 2.3 61.1 28.3 0.2 8.1 20.6 22.0 3.6 53.8 54.5 45.5

2005 2.2 64.5 25.7 0.2 7.4 10.9 14.4 4.9 69.8 37.0 63.0

2007 2.4 67.6 23.2 0.2 6.6 14.5 23.5 4.1 57.9 38.6 61.4

2007 2.7 70.6 20.6 0.2 5.9 14.7 27.5 3.8 54.0 49.4 50.6

2008 2.7 73.9 18.0 0.2 5.2 17.1 38.7 3.0 41.2 69.2 30.8

2009 2.8 77.2 15.4 0.1 4.4 13.9 38.1 3.2 44.8 65.4 34.6

2010 2.6 80.8 12.8 0.1 3.7 13.4 43.3 3.0 40.3 64.9 35.1

2011 3.1 83.7 10.2 0.1 2.9 10.6 40.3 3.3 45.7 61.7 38.3

2012 3.1 87.0 7.6 0.1 2.2 11.5 50.8 2.6 35.1 75.8 24.2

2013 3.3 90.2 5.0 0.0 1.4 10.1 51.2 2.7 36.0 9.5 90.5

2014 4.1 92.6 2.5 0.0 0.7 6.8 38.7 3.7 50.8 1.0 99.0

2015 3.8 96.2 NO NO NO 8.7 54.9 2.5 33.9 0.7 99.3

2016 3.7 96.3 NO NO NO 5.7 39.9 3.9 50.6 NO 100.0

2017 3.7 96.3 NO NO NO 4.3 33.4 4.7 57.6 NO 100.0

2018 4.1 95.9 NO NO NO 3.8 31.2 5.0 60.1 NO 100.0

NO…not occurring * including industrial waste

1.A.4.b.1 Residential: stationary

Energy consumption by type of fuel and by type of heating is derived from an energy demand model for space heating based on heating market surveys validated with a statistical evaluation of micro census data 1990, 1992, 1999/2000, 2004, 2006, 2008, 2010, 2012, 2014, 2016 and 2018 (STATISTIK AUSTRIA 1990, 1992b, 2002 & 2019b). The calculated shares are used to sub-divide total final energy consumption to the several technologies. For the years in between the



shares are interpolated. Because the newest census data is always reconsidered to improve pre-vious years’ census data evaluation this implies a periodic recalculation in time series. The energy demand model is calibrated according to the energy statistics supplier (see section Activity data above).

Table 135: Fuel consumption from NFR 1.A.4.b.1 Residential: stationary 1990–2018.

NFR 1.A.4.b.1 1.A.4.b.1 1.A.4.b.1 1.A.4.b.1 1.A.4.b.1 1.A.4.b.1 Fuel (PJ) liquid solid gaseous biomass other

1990 190.86 72.50 26.62 33.34 58.40 NO

1991 213.14 79.16 29.12 39.82 65.04 NO

1992 198.04 72.69 25.06 38.79 61.50 NO

1993 199.95 73.98 20.81 42.37 62.79 NO

1994 185.98 69.12 18.52 40.17 58.16 NO

1995 199.14 75.59 17.56 43.19 62.80 NO

1996 218.05 83.89 16.64 48.58 68.94 NO

1997 193.54 68.05 12.58 48.52 64.39 NO

1998 196.62 71.31 11.05 51.37 62.89 NO

1999 198.32 73.12 10.22 50.92 64.06 NO

2000 189.20 72.60 9.05 47.49 60.07 NO

2001 197.02 71.55 8.57 53.11 63.79 NO

2002 185.37 68.92 6.87 49.83 59.73 NO

2003 186.78 69.07 5.78 52.81 59.11 NO

2004 180.77 66.55 5.49 51.84 56.89 NO

2005 194.25 63.88 3.97 67.58 58.82 0.00

2006 192.71 61.36 3.77 65.64 61.93 0.00

2007 177.58 53.50 3.22 57.59 63.27 0.00

2008 181.47 54.33 3.28 59.16 64.69 0.00

2009 180.26 50.63 2.39 60.39 66.85 0.00

2010 199.33 55.88 2.63 65.44 75.38 0.00

2011 179.86 48.34 1.69 58.12 71.71 0.00

2012 180.81 44.01 1.77 59.22 75.81 0.00

2013 187.22 47.32 1.35 59.84 78.70 0.00

2014 163.53 41.46 1.13 51.93 69.00 0.00

2015 172.77 43.18 0.91 56.54 72.12 0.00

2016 179.83 42.84 0.87 62.41 73.72 0.00

2017 180.43 43.35 0.94 61.52 74.62 0.00

2018 164.43 39.07 0.84 56.58 67.94 0.00 Trend 1990–2018

-13.8% -46.1% -96.8% 69.7% 16.3% NO

Trend 2017–2018

-8.9% -9.9% -10.8% -8.0% -8.9% 0.4%



Table 136: Share of 1.A.4.b heating type on fuel category for the year 2018.

Fuel No. Heating type Share of heating type [% TJ]

1.A.4.b

Light fuel oil #1 Fuel oil boilers NO

Medium fuel oil #1 Fuel oil boilers NO

Heavy fuel oil #1 Fuel oil boilers NO

Diesel #1 Fuel oil boilers NO

Petroleum #1 Fuel oil boilers NO

Gas oil #2 #3 #4 #5

#6

Gas oil stoves Vaporizing burners Yellow burners Blue burners with conventional technology Blue burners with low temperature or condensing technology

2.0% 0.3%

45.7% 1.6%

50.4%

Natural gas #7 #8 #9

Natural gas convectors Atmospheric burners Forced-draft natural gas burners

10.1% 46.5% 43.4%

Biogas and landfill gas #8 #9

Atmospheric burners Forced-draft natural gas burners

NO NO

LPG and gas works gas #10 #11

LPG stoves LPG boilers

13.1% 86.9%

Fuel wood #12 #13

#14 #15 #16

Wood stoves and cooking stoves Tiled wood stoves and masonry heaters Mixed-fuel wood boilers Natural-draft wood boilers Forced-draft wood boilers

9.5% 8.4%

46.3% 5.6%

30.2%

Wood waste #17

#18

#19 #20

Wood chips boilers with conventional technology Wood chips boilers with oxygen sensor emission control Pellet stoves Pellet boilers

4.7%

35.1%

2.5% 57.7%

Hard coal and hard coal briquettes

#21 #22


23.0% 77.0%

Lignite and brown coal #21 #22


23.0% 77.0%

Brown coal briquettes #21 #22


23.0% 77.0%

Coke #21 #22


23.0% 77.0%

Peat #21 #22


NO NO

Industrial waste #22 Coal boilers NO

Char coal BBQ Barbecue 100.0%




Table 137: NFR 1.A.4.b.1 percentual consumption by type of heating.

Fuel (group) Natural Gas Fuel Oil, LPG Gasoil

Heating type No. #7 #8 #9 #1 #10 #11 #2 #3 #4 #5 #6


1990 39.1 53.5 7.5 96.3 0.8 2.8 15.0 11.0 64.8 1.5 7.7

1991 37.6 53.9 8.5 95.1 1.0 3.9 15.0 10.8 63.0 1.6 9.5

1992 36.1 54.3 9.7 94.6 1.0 4.4 14.4 10.7 61.6 1.9 11.4

1993 34.6 54.5 10.9 90.9 1.6 7.5 13.8 10.5 60.0 2.3 13.4

1994 33.0 54.7 12.2 87.6 2.0 10.4 13.3 10.2 58.4 3.0 15.2

1995 31.5 54.9 13.6 86.7 1.9 11.4 12.7 9.8 56.8 3.8 17.0

1996 30.0 55.0 15.0 85.8 1.7 12.4 12.1 9.3 55.2 4.8 18.6

1997 28.5 55.0 16.5 84.6 1.8 13.6 11.5 8.9 53.6 5.8 20.2

1998 27.0 55.0 17.9 84.2 1.8 14.0 10.9 8.5 52.6 6.5 21.5

1999 25.5 55.0 19.5 84.3 1.6 14.1 10.4 8.1 51.7 7.1 22.7

2000 24.0 55.1 20.9 80.5 2.0 17.5 10.4 7.8 50.7 7.5 23.6

2001 22.5 55.3 22.2 82.9 1.5 15.6 9.1 7.6 50.7 8.0 24.6

2002 21.0 55.5 23.5 81.6 1.7 16.7 7.9 7.5 50.9 8.2 25.4

2003 19.5 55.9 24.6 85.2 1.3 13.5 6.7 7.5 51.3 8.4 26.1

2004 18.0 56.3 25.8 84.9 1.4 13.7 4.8 7.6 52.2 8.7 26.8

2005 15.8 56.7 27.5 70.1 2.5 27.4 4.2 7.2 52.3 8.3 28.0

2007 15.6 55.8 28.6 68.3 2.7 29.0 3.6 6.9 52.4 7.9 29.2

2007 15.6 54.8 29.6 59.3 3.7 37.1 3.0 6.5 52.3 7.5 30.6

2008 15.0 54.1 30.9 59.0 4.2 36.8 2.9 6.1 51.9 7.0 32.1

2009 14.4 53.4 32.2 53.5 5.7 40.8 2.8 5.6 51.3 6.5 33.7

2010 14.2 52.4 33.5 45.1 6.5 48.4 2.7 5.1 51.0 6.0 35.3

2011 14.5 50.9 34.6 32.2 9.3 58.4 2.5 4.5 50.3 5.4 37.3

2012 12.3 50.8 36.9 19.1 10.4 70.5 2.4 3.9 49.8 4.8 39.1

2013 10.4 50.3 39.3 12.3 10.8 76.9 2.3 3.3 49.1 4.1 41.2

2014 11.2 48.3 40.4 NO 15.7 84.3 2.4 2.6 48.4 3.3 43.3

2015 10.7 47.7 41.6 NO 15.6 84.4 2.3 1.8 47.7 2.5 45.7

2016 10.2 47.0 42.8 NO 14.0 86.0 2.1 1.0 47.3 1.8 47.8

2017 9.9 46.7 43.4 NO 12.9 87.1 2.0 0.5 46.6 1.7 49.2

2018 10.1 46.5 43.4 NO 13.1 86.9 2.0 0.3 45.7 1.6 50.4

NO…not occurring



Table 138: NFR 1.A.4.b.1 percentual consumption by type of heating (continued).

Fuel (group) Fuel Wood (log wood) Wood chips, pellets and other biomass

Coal (+ Briquettes)

Heating type No. #12 #13 #14 #15 #16 #17 #18 #19 #20 #21 #22


1990 27.2 4.1 66.2 NO 2.5 88.0 12.0 NO NO 30.0 70.0

1991 25.5 5.5 65.7 NO 3.4 70.0 11.7 NO 18.3 29.3 70.7

1992 23.2 6.9 65.4 NO 4.5 57.9 12.3 NO 29.8 28.6 71.4

1993 21.0 8.3 65.0 NO 5.7 49.5 13.1 NO 37.4 28.0 72.0

1994 19.2 9.3 64.5 NO 7.0 43.2 13.9 NO 42.9 27.3 72.7

1995 17.6 10.1 64.1 NO 8.2 38.6 14.4 NO 47.0 26.6 73.4

1996 16.0 10.8 63.6 NO 9.6 34.8 15.1 NO 50.1 25.9 74.1

1997 14.7 11.2 63.1 NO 10.9 31.5 15.9 NO 52.7 25.2 74.8

1998 13.7 11.5 62.7 NO 12.2 28.5 16.7 NO 54.8 24.5 75.5

1999 12.6 11.7 62.1 NO 13.6 26.0 17.5 NO 56.5 23.8 76.2

2000 12.5 11.8 60.8 NO 14.9 23.6 18.4 NO 58.1 23.1 76.9

2001 12.0 9.9 61.5 NO 16.6 27.9 25.3 0.2 46.5 22.4 77.6

2002 11.1 8.4 62.2 0.1 18.2 30.9 32.2 1.1 35.8 21.7 78.3

2003 9.9 7.2 62.9 0.3 19.8 32.7 38.6 1.6 27.0 21.1 78.9

2004 10.1 6.9 61.8 0.5 20.7 28.5 38.3 1.8 31.5 20.4 79.6

2005 9.1 6.7 60.9 0.9 22.4 23.6 38.4 2.0 36.0 18.3 81.7

2007 9.5 7.2 58.1 1.6 23.6 18.4 35.5 2.4 43.7 18.4 81.6

2007 10.1 7.8 56.0 2.1 24.0 15.2 33.3 2.6 49.0 18.6 81.4

2008 9.6 7.8 55.4 2.7 24.5 13.5 34.6 2.6 49.3 16.7 83.3

2009 9.1 8.0 54.4 3.2 25.4 10.7 32.2 3.0 54.1 14.2 85.8

2010 8.8 8.1 53.4 3.6 26.1 8.4 29.0 3.3 59.2 18.0 82.0

2011 8.5 7.8 52.5 4.0 27.1 6.5 25.7 3.3 64.5 24.0 76.0

2012 8.7 8.1 51.1 4.3 27.8 5.0 22.2 3.0 69.8 23.7 76.3

2013 9.0 8.3 49.8 4.6 28.3 7.1 35.6 1.9 55.3 22.8 77.2

2014 9.3 8.7 48.6 4.8 28.7 6.5 35.6 1.9 56.0 20.9 79.1

2015 9.5 9.2 47.3 5.0 28.9 6.2 37.6 2.0 54.1 18.7 81.3

2016 9.3 9.1 46.9 5.2 29.5 5.4 35.8 2.2 56.6 20.3 79.7

2017 9.3 8.8 46.6 5.4 29.9 4.7 33.2 2.4 59.7 21.7 78.3

2018 9.5 8.4 46.3 5.6 30.2 4.7 35.1 2.5 57.7 23.0 77.0

NO…not occurring



Figure 37 shows activity data of 1.A.4.b.1 Residential: stationary by type of fuel together with the correlating heating degree days for the years 1990 to 2018 (ZAMG 2019).

Figure 37: Energy consumption [PJ] of residential sector by type of fuel and number of heating degree days 1990–2018.

1.A.4.c.1 Agriculture/Forestry/Fishing: stationary

The fuel consumption reported in (IEA JQ 2019) for category 1.A.4.c.1 is predominantly as-signed to implied emission factors derived from category 1.A.4.a.1 assuming similar structure of heating types in both categories (see section Activity data above).

Table 139: Fuel consumption from NFR 1.A.4.c.1 Agriculture/Forestry/Fishing: Stationary 1990–2018.

NFR 1.A.4.c 1 1.A.4.c 1 1.A.4.c 1 1.A.4.c 1 1.A.4.c 1 1.A.4.c 1 Fuel (PJ) liquid solid gaseous biomass other

1990 10.26 5.34 0.55 0.37 4.01 NO

1991 10.25 4.71 0.61 0.44 4.49 NO

1992 9.50 4.21 0.56 0.43 4.29 NO

1993 8.23 2.89 0.44 0.47 4.42 NO

1994 6.96 2.10 0.39 0.45 4.01 NO

1995 7.68 2.30 0.39 0.49 4.49 NO

1996 8.46 2.60 0.37 0.55 4.95 NO

1997 8.40 2.70 0.30 0.56 4.83 NO

1998 8.28 2.87 0.24 0.61 4.56 NO

1999 9.08 3.17 0.23 0.58 5.10 NO

0

500

1.000

1.500

2.000

2.500

3.000

3.500

4.000

0

50

100

150

200

250

1990

1995

2000

2005

2010

2015

2018

Hea

ting

degr

ee d

ays

PJ

Energy consumption of residential sector

District heating

biomass

gaseous

solid

liquid

Heating degree days

Source: IEA JQ (2019), ZAMG (2019), Umweltbundesamt



NFR 1.A.4.c 1 1.A.4.c 1 1.A.4.c 1 1.A.4.c 1 1.A.4.c 1 1.A.4.c 1 Fuel (PJ) liquid solid gaseous biomass other

2000 8.46 2.79 0.18 0.54 4.95 NO

2001 9.09 2.73 0.16 0.60 5.60 NO

2002 8.32 2.28 0.12 0.56 5.36 NO

2003 8.90 2.56 0.09 0.59 5.66 NO

2004 9.13 2.44 0.09 0.58 6.03 NO

2005 8.11 1.47 0.12 0.77 5.75 NO

2006 7.84 1.34 0.11 0.73 5.67 NO

2007 7.29 1.02 0.13 0.74 5.40 NO

2008 7.48 1.04 0.14 0.75 5.54 NO

2009 7.06 0.62 0.05 0.74 5.64 NO

2010 7.80 0.53 0.06 0.84 6.37 NO

2011 7.30 0.42 0.04 0.72 6.13 NO

2012 7.59 0.42 0.04 0.46 6.66 NO

2013 8.34 0.53 0.03 0.51 7.28 NO

2014 7.84 0.56 0.03 0.55 6.70 NO

2015 8.33 0.50 0.02 0.62 7.19 NO

2016 8.44 0.60 0.02 0.74 7.09 NO

2017 8.73 0.28 0.03 1.01 7.41 NO

2018 7.90 0.25 0.02 0.91 6.71 NO Trend 1990–2018

-23.0% -95.4% -95.5% 150.1% 67.6% NO

Trend 2016–2018

-9.5% -10.5% -11.0% -10.0% -9.4% NO

3.1.9.2 Emission factors for main pollutants

Due to the wide variation of technologies, fuel quality and device maintenance the uncertainty of emission factors is rather high for almost all pollutants and technologies.

Country specific main pollutant emission factors from national studies (BMWA 1990, 1996 and 1999) and (UMWELTBUNDESAMT 2001a) are applied. In these studies emission factors are pro-vided for the years 1987, 1995 and 1996. Emission factors prior to 1996 are taken from (STANZEL et al. 1995) and mainly based on literature research.

Natural gas and heating oil emission factors 1996 are determined by means of test bench meas-urements of boilers and stoves sold in Austria. Solid fuels emission factors 1996 are determined by means of field measurements of Austrian small combustion devices.

For the years 1990 to 1994 emission factors were interpolated. From 1997 onwards the emission factors from 1996 are applied.

In some cases only VOC emission factors are provided in the studies, NMVOC emission factors are determined assuming that a certain percentage of VOC emissions is released as methane as listed in Table 140. The split follows closely (STANZEL et al. 1995).



Table 140: Share of CH4 and NMVOC in VOC for small combustion devices.

CH4 NMVOC VOC

Coal 25% 75% 100%

Gas oil; Kerosene 20% 80% 100%

Residual fuel oil 25% 75% 100%

Natural gas; LPG 80% 20% 100%

Biomass 25% 75% 100%

Additional literature research based on (UMWELTBUNDESAMT 2017c) was done to reflect the twenty-two technology and fuel dependent main sub categories (heating types):

Supplemental CO emission factors are taken from the EMEP/EEA Air Pollutant Emission In-ventory Guidebook 2016, the Fact Sheet of the Swiss Federal Office for the Environment (FOEN 2015) and (LANG et al. 2003).

Supplemental NMVOC emission factors are taken from the EMEP/EEA Air Pollutant Emis-sion Inventory Guidebook 2013 and 2016, (LANG et al. 2003) and (GERMAN ENVIRONMENT AGENCY 2008).

Supplemental NOx emission factors are taken from the EMEP/EEA Air Pollutant Emission In-ventory Guidebook 2016, the Fact Sheet of the Swiss Federal Office for the Environment (FOEN 2015), (LEUTGÖB et al. 2003) and (GERMAN ENVIRONMENT AGENCY 2008).

Supplemental SO2 emission factors are taken from the EMEP/EEA Air Pollutant Emission In-ventory Guidebook 2016 and (LEUTGÖB et al. 2003).

Supplemental NH3 emission factors are taken from the EMEP/CORINAIR Emission Inventory Guidebook – 2006 and (UMWELTBUNDESAMT 1993).

The following table shows biomass share of wood stoves and cooking stoves stock from 2001 which are considered with lower CO, NMVOC and CH4 emissions than equipment installed be-fore 2001. The selected factors are derived from the energy demand model for space heating.

Table 141: Share of wood stoves and cooking stoves stock 2001–2018.

Year Wood stoves and cooking stoves (new) Wood stoves and cooking stoves (conventional)

1.A.4.a 1.A.4.b 1.A.4.a 1.A.4.b 2001 1.3% 1.0% 98.7% 99.0% 2002 2.5% 2.1% 97.5% 97.9% 2003 3.6% 3.2% 96.4% 96.8% 2004 4.8% 4.3% 95.2% 95.7% 2005 5.9% 5.4% 94.1% 94.6% 2006 7.1% 6.5% 92.9% 93.5% 2007 8.3% 7.6% 91.7% 92.4% 2008 9.4% 8.7% 90.6% 91.3% 2009 10.6% 9.7% 89.4% 90.3% 2010 11.7% 10.8% 88.3% 89.2% 2011 12.9% 11.9% 87.1% 88.1% 2012 14.1% 13.0% 85.9% 87.0% 2013 15.2% 14.1% 84.8% 85.9%



Year Wood stoves and cooking stoves (new) Wood stoves and cooking stoves (conventional)

1.A.4.a 1.A.4.b 1.A.4.a 1.A.4.b 2014 16.4% 15.2% 83.6% 84.8% 2015 17.5% 16.3% 82.5% 83.7% 2016 18.7% 17.4% 81.3% 82.6% 2017 19.9% 18.4% 80.1% 81.6% 2018 21.0% 19.5% 79.0% 80.5%

Table 142: NMVOC, CH4 and CO emission factors of category 1.A.4 new wood stoves and cooking stoves (Source: LANG et al. 2003).

Fuel No. NMVOC [kg/TJ]

CH4 [kg/TJ]

CO [kg/TJ]

1.A.4.a/b 1.A.4.a/b 1.A.4.a/b

Fuel wood #12 338.00 115.61 2 345.30

The following table shows biomass share of mixed-fuel wood boilers stock with (comparatively) advanced technology which are considered with (slightly) lower NOx, CO, NMVOC and CH4

emissions than conventional equipment. The selected factors are derived from the energy de-mand model for space heating.

Table 143: Share of mixed-fuel wood boilers stock 1990–2018.

Year Mixed-fuel wood boilers (advanced) Mixed-fuel wood boilers (conventional) 1.A.4.a 1.A.4.b 1.A.4.a 1.A.4.b 1990 3.8% 3.7% 96.2% 96.3% 1991 4.3% 4.2% 95.7% 95.8% 1992 4.7% 4.7% 95.3% 95.3% 1993 5.2% 5.3% 94.8% 94.7% 1994 5.7% 5.9% 94.3% 94.1% 1995 6.1% 6.4% 93.9% 93.6% 1996 6.5% 7.0% 93.5% 93.0% 1997 7.0% 7.7% 93.0% 92.3% 1998 7.4% 8.3% 92.6% 91.7% 1999 7.8% 8.8% 92.2% 91.2% 2000 8.1% 9.3% 91.9% 90.7% 2001 8.5% 9.8% 91.5% 90.2% 2002 8.7% 10.0% 91.3% 90.0% 2003 8.8% 10.2% 91.2% 89.8% 2004 8.8% 10.3% 91.2% 89.7% 2005 9.1% 10.3% 90.9% 89.7% 2006 9.2% 10.5% 90.8% 89.5% 2007 9.3% 10.6% 90.7% 89.4% 2008 9.5% 10.6% 90.5% 89.4% 2009 9.7% 10.7% 90.3% 89.3% 2010 9.8% 10.8% 90.2% 89.2% 2011 9.9% 10.9% 90.1% 89.1%



Year Mixed-fuel wood boilers (advanced) Mixed-fuel wood boilers (conventional) 1.A.4.a 1.A.4.b 1.A.4.a 1.A.4.b 2012 10.1% 11.0% 89.9% 89.0% 2013 10.2% 11.1% 89.8% 88.9% 2014 10.4% 11.2% 89.6% 88.8% 2015 10.5% 11.2% 89.5% 88.8% 2016 10.7% 11.3% 89.3% 88.7% 2017 10.8% 11.4% 89.2% 88.6% 2018 10.9% 11.4% 89.1% 88.6%

Table 144: NOx, NMVOC, CH4 and CO emission factors of category 1.A.4 advanced mixed-fuel wood boilers (Source: BMWA 1999, EMEP/EEA Air Pollutant Emission Inventory Guidebook 2016).

Fuel No. NOx [kg/TJ]

NMVOC [kg/TJ]

CH4 [kg/TJ]

CO [kg/TJ]

1.A.4.a/b 1.A.4.a/b 1.A.4.a/b 1.A.4.a/b

Fuel wood #14 107.0 350.00 121.4 3 483.00

The following table shows gas oil share of blue burners with low temperature or condensing technology stock from 2001 which are considered with lower NOx emissions than equipment in-stalled before 2001. New installations reflect the market entrance of condensing boiler technol-ogy. The selected factors are derived from the energy demand model for space heating.

Table 145: Share of new blue burners with low temperature or condensing technology stock 2001–2018.

Year Blue burners with low temperature or condensing technology (new)

Blue burners with low temperature or condensing technology (conventional)

1.A.4.a 1.A.4.b 1.A.4.a 1.A.4.b 2001 0.3% 1.8% 99.7% 98.2% 2002 1.5% 3.0% 98.5% 97.0% 2003 2.7% 4.2% 97.3% 95.8% 2004 3.9% 5.3% 96.1% 94.7% 2005 5.1% 6.4% 94.9% 93.6% 2006 6.3% 7.5% 93.7% 92.5% 2007 7.5% 8.6% 92.5% 91.4% 2008 8.7% 9.8% 91.3% 90.2% 2009 9.9% 10.9% 90.1% 89.1% 2010 11.2% 12.0% 88.8% 88.0% 2011 12.4% 13.1% 87.6% 86.9% 2012 13.6% 14.2% 86.4% 85.8% 2013 14.8% 15.4% 85.2% 84.6% 2014 16.0% 16.5% 84.0% 83.5% 2015 17.2% 17.6% 82.8% 82.4% 2016 18.4% 18.7% 81.6% 81.3% 2017 19.6% 19.8% 80.4% 80.2% 2018 20.8% 21.0% 79.2% 79.0%



Table 146: NOx emission factors of category 1.A.4 new blue burners with low temperature or condensing technology (Source: LEUTGÖB et al. 2003).


1.A.4.a/b Gas oil #6 20.0

Desulphurisation of gas oil reduced the organic nitrogen content down to 10 ppm from 2009 onwards. This is reflected by lowering NOx emission factors for all boilers burning gas oil by about 10.7% in the year 2009.

The following table shows natural gas share of forced-draft natural gas burners stock from 2001 which are considered with lower NOx emissions than equipment installed before 2001. New in-stallations reflect the market entrance of condensing boiler technology. The selected factors are derived from the energy demand model for space heating.

Table 147: Share of new forced-draft natural gas burners stock 2001–2018.

Year Forced-draft natural gas burners (new) Forced-draft natural gas burners (conventional)

1.A.4.a 1.A.4.b 1.A.4.a 1.A.4.b

2001 0.2% 1.5% 99.8% 98.5%

2002 1.4% 2.6% 98.6% 97.4%

2003 2.6% 3.7% 97.4% 96.3%

2004 3.9% 4.8% 96.1% 95.2%

2005 5.1% 5.9% 94.9% 94.1%

2006 6.4% 7.1% 93.6% 92.9%

2007 7.6% 8.2% 92.4% 91.8%

2008 8.8% 9.3% 91.2% 90.7%

2009 10.1% 10.4% 89.9% 89.6%

2010 11.3% 11.6% 88.7% 88.4%

2011 12.5% 12.7% 87.5% 87.3%

2012 13.8% 13.8% 86.2% 86.2%

2013 15.0% 15.0% 85.0% 85.0%

2014 16.3% 16.1% 83.7% 83.9%

2015 17.5% 17.2% 82.5% 82.8%

2016 18.7% 18.3% 81.3% 81.7%

2017 20.0% 19.5% 80.0% 80.5%

2018 21.2% 20.6% 78.8% 79.4%

Table 148: NOx emission factors of category 1.A.4 new forced-draft natural gas burners (Source: LEUTGÖB

et al. 2003).


1.A.4.a/b Natural gas #9 16.0



For category 1.A.4.c.1 fuel consumption reported in (IEA JQ 2019) is assigned to implied emis-sion factors derived from category 1.A.4.a.1 assuming similar structure of heating types in both categories. Supplemental implied emission factors derived from category 1.A.4.b.1 were as-signed, if no activity data for the specific fuel in category 1.A.4.a.1 occurred.

The following tables show the main pollutant emission factors by type of heating.



Table 149: NFR 1.A.4. NOx emission factors for the year 2018.

No. Heating type Fuel Emission factors NOx [kg/TJ]

1.A.4.a 1.A.4.b 1.A.4.c

#1 Fuel oil boilers

Residual fuel oil Diesel Petroleum, other petroleum products

115.0 700.0

NO

NO NO NO

115.0 NO NO

#2 Gas oil stoves Gas oil 48.0 48.0

36.4(1)

#3 Vapourizing burners Gas oil 61.6 61.6

#4 Yellow burners Gas oil 37.5 37.5

#5 Blue burners with conventional technology Gas oil 36.6 36.6

#6 Blue burners with low temperature or condensing technology Gas oil 33.2 33.1

#7 Natural gas convectors Natural gas 51.0 51.0

41.8(1) #8 Atmospheric burners Natural gas Biogas and landfill gas

42.0 150.0

42.0 NO

#9 Forced-draft natural gas burners Natural gas Biogas and landfill gas

36.5 150.0

36.6 NO

#10 LPG stoves LPG and gas works gas 51.0 51.0 48.7(1)

#11 LPG boilers LPG and gas works gas 44.0 44.0

#12 Wood stoves and cooking stoves Fuel wood Char coal

106.0 40.0

106.0 40.0

81.1(1) #13 Tiled wood stoves and masonry

heaters Fuel wood 80.0 80.0

#14 Mixed-fuel wood boilers Fuel wood NO 122.1

#15 Natural-draft wood boilers Fuel wood NO 107.0

#16 Forced-draft wood boilers Fuel wood NO 80.0

#17 Wood chips boilers with conventional technology Wood waste 107.0 107.0

68.0(1) #18 Wood chips boilers with oxygen sensor emission control Wood waste 80.0 80.0

#19 Pellet stoves Wood waste 60.0 60.0

#20 Pellet boilers Wood waste 60.0 60.0

#21 Coal stoves

Hard coal and hard coal briquettes Lignite and brown coal Brown coal briquettes Coke Peat

NO

NO NO NO NO

132.0

132.0 132.0 132.0

NO 90.4(1)

#22 Coal boilers

Hard coal and hard coal briquettes Lignite and brown coal Brown coal briquettes Coke Industrial waste

NO

NO NO NO

100.0

78.0

78.0 78.0 78.0 NO

NO…not occurring (in 2018) (1) Implied emission factor



Table 150: NFR 1.A.4. NMVOC emission factors for the year 2018.

No. Heating type Fuel Emission factors NMVOC [kg/TJ]

1.A.4.a 1.A.4.b 1.A.4.c

#1 Fuel oil boilers


0.75 0.80 NO

NO NO NO

0.75 NO NO


0.80






0.69(1) #8 Atmospheric burners Natural gas Biogas and landfill gas

0.51 0.51

0.51 NO


0.20 0.20

0.20 NO

#10 LPG stoves LPG and gas works gas 2.00 2.00 1.50(1)



579.05 2 000.00

583.59 2 000.00










#21 Coal stoves


NO

NO NO NO NO

333.30

333.30 333.30 333.30

NO 295.64(1)

#22 Coal boilers


NO

NO NO NO

0.54

284.40

284.40 284.40 284.40

NO




Table 151: NFR 1.A.4. CO emission factors for the year 2018.

No. Heating type Fuel Emission factors CO [kg/TJ]

1.A.4.a 1.A.4.b 1.A.4.c

#1 Fuel oil boilers


45.0 15.0 NO

NO NO NO

45.0 NO NO


67.0






37.0 #8 Atmospheric burners Natural gas Biogas and landfill gas

48.0 48.0

48.0 NO


37.0 37.0

37.0 NO

#10 LPG stoves LPG and gas works gas 80.0 80.0 37.0



3 891.5(1)

8 100.0 3 920.6(1)

8 100.0

2 408.9(2) #13 Tiled wood stoves and masonry

heaters Fuel wood 2 345.3(1) 2 345.3(1)

#14 Mixed-fuel wood boilers Fuel wood NO 4 209.4

#15 Natural-draft wood boilers Fuel wood NO 3 483.0(1)

#16 Forced-draft wood boilers Fuel wood NO 3 234.2(1)

#17 Wood chips boilers with conventional technology Wood waste 2 400.0 2 400.0

460.8(2) #18 Wood chips boilers with oxygen sensor emission control Wood waste 776.2(1) 776.2(1)

#19 Pellet stoves Wood waste 402.5(1) 402.5(1)

#20 Pellet boilers Wood waste 180.4(1) 180.4(1)

#21 Coal stoves


NO

NO NO NO NO

3 705.0

3 705.0 3 705.0 3 705.0

NO 4 206.0

#22 Coal boilers


NO

NO NO NO

200.0

4 206.0

4 206.0 4 206.0 4 206.0

NO

NO…not occurring (in 2018) (1) CO from new biomass heatings is calculated by means of ratio of NMVOC from new by conventional heatings (2) Implied emission factor



Table 152: NFR 1.A.4. SO2 emission factors for the year 2018.

No. Heating type Fuel Emission factors SO2 [kg/TJ]

1.A.4.a 1.A.4.b 1.A.4.c

#1 Fuel oil boilers


90.00 18.76

NO

NO NO NO

90.0 NO NO


0.47







0.30 NA

0.30 NO


0.30 NA

0.30 NO



#12 Wood stoves and cooking stoves Fuel wood

Char coal 11.00 11.00

11.00 #13 Tiled wood stoves and masonry






11.00 #18 Wood chips boilers with oxygen sensor emission control Wood waste 11.00 11.00



#21 Coal stoves


NO

NO NO NO NO

543.00

543.00 543.00 543.00

NO 543.00

#22 Coal boilers


NO

NO NO NO

130.00

543.00

543.00 543.00 543.00

NO

NA…not applicable NO…not occurring (in 2018)



Table 153: NFR 1.A.4. NH3 emission factors for the year 2018.

No. Heating type Fuel Emission factors NH3 [kg/TJ]

1.A.4.a 1.A.4.b 1.A.4.c

#1 Fuel oil boilers


2.68 2.68 NO

NO NO NO

2.68 NO NO


2.68







1.00 1.00

1.00 NO


1.00 1.00

1.00 NO



#12 Wood stoves and cooking stoves Fuel wood Char coal 5.00 5.00










#21 Coal stoves


NO

NO NO NO NO

0.0089

0.023 0.023

0.0088 NO

0.0181)

#22 Coal boilers


NO

NO NO NO

0.023

0.0089

0.023 0.023

0.0088 NO





Fuel Oil

For fuel oil the same emission factors as for 1.A.1 were used.

Coal and Biomass

NFR 1.A.4.c

For deciding on an emission factor for fuel wood results from (OBERNBERGER 1995), (LAUNHARDT et al. 2000) and (FTU 2000) were considered.

The emission factors for coal were derived from (CORINAIR 1995), Table 12, B112.

NFR 1.A.4.b

Emission factors for category 1.A.4.b are based on findings from (HARTMANN, BÖHM & MAIER 2000), (LAUNHARDT, HARTMANN, LINK & SCHMID 2000), (PFEIFFER, STRUSCHKA & BAUMBACH 2000), (STANZEL et al. 1995).

Results of measurements (SPITZER et al. 1998): show that the TSP emission factor for stoves are about 50% higher than the emission factor for central heating boilers – thus the Cd and Pb emission factor was also assumed to be 50% higher.

Natural gas

Emission factors for heating types burning natural gas, biogas and landfill gas are taken from the EMEP/EEA Air Pollutant Emission Inventory Guidebook 2016 based on (UMWELTBUNDESAMT 2017c).



Table 154: NFR 1.A.4. Cd emission factors for the year 2018.

No. Heating type Fuel Emission factors Cd [g/TJ]

1.A.4.a 1.A.4.b 1.A.4.c

#1 Fuel oil boilers


0.05 0.02 NO

NO NO NO

0.05 NO NO


0.02






NE #8 Atmospheric burners Natural gas Biogas and landfill gas

0.00025 0.00025

0.00025 NO


0.00025 0.00025

0.00025 NO

#10 LPG stoves LPG and gas works gas 0.02 0.02 NE












#21 Coal stoves


NO

NO NO NO NO

6.00

3.00 3.00 6.00 NO

4.30(1)

#22 Coal boilers


NO

NO NO NO

7.00

4.00

2.00 2.00 4.00 NO

NO…not occurring (in 2018) NE…not estimated NA…not applicable (1) Implied emission factor



Table 155: NFR 1.A.4. Hg emission factors for the year 2018.

No. Heating type Fuel Emission factors Hg [g/TJ]

1.A.4.a 1.A.4.b 1.A.4.c

#1 Fuel oil boilers


0.015 0.007

NO

NO NO NO

0.015 NO NO


0.007







0.10 0.10

0.10 NO


0.10 0.10

0.10 NO













#21 Coal stoves


NO

NO NO NO NO

10.70

9.20 9.20

10.70 NO

9.73(1)

#22 Coal boilers


NO

NO NO NO

2.00

10.70

9.20 9.20

10.70 NO

NO…not occurring (in 2018) NA…not applicable (1) Implied emission factor



Table 156: NFR 1.A.4. Pb emission factors for the year 2018.

No. Heating type Fuel Emission factors Pb [g/TJ]

1.A.4.a 1.A.4.b 1.A.4.c

#1 Fuel oil boilers


0.05 0.02 NO

NO NO NO

0.05 NO NO


0.02







0.0015 0.0015

0.0015 NO


0.0015 0.0015

0.0015 NO













#21 Coal stoves


NO

NO NO NO NO

135.00

33.00 33.00

135.00 NO

45.90(1)

#22 Coal boilers


NO

NO NO NO

50.00

90.00

22.00 22.00 90.00

NO





1.A.4.a.1 Commercial/Institutional: stationary and 1.A.4.b.1 Residential: stationary

For categories 1.A.4.a.1 and 1.A.4.b.1 the dioxin emission factors for coal and wood were taken from (HÜBNER & BOOS 2000). For vapourizing burners, tiled wood stoves and masonry heaters, natural-draft wood boilers and pellet stoves the EMEP/EEA Air Pollutant Emission Inventory Guidebook 2016 was considered. For heating oil a mean value from (PFEIFFER et al. 2000), (BOOS & HÜBNER 1999) measurements by FTU (FTU 2000) and the EMEP/EEA Guidebook 2016 was used. Combustion of waste in residential plants was not considered, as no activity data was available. HCB emission factors are taken from the EMEP/EEA Air Pollutant Emission Inventory Guide-book 2016, the national study (HÜBNER et al. 2002) and based on field measurements from 15 solid fuel residential boilers and stoves with a capacity less than 50 kW using the standard methodology according to ÖNORM EN-1948-1. The results show a high variation in flue gas concentrations without any correlation between type of heating (stove, boiler) or fuel (log wood, pellets, wood chips, coal). Inter alia for commercial and institutional plants the same emission factors as used for small (and medium) plants of category 1.A.2 were chosen (the share of the different size classes is based on expert judgement). The PAH emission factors are trimmed mean values from values given in (UBA BERLIN 1998), (SCHEIDL 1996), (ORTHOFER & VESELY 1990), (SORGER 1993), (LAUNHARDT et al. 2000), (PFEIFFER et al. 2000) (LAUNHARDT et al. 1998), (STANZEL et al. 1995), (BAAS et al. 1995). How-ever, it was not possible to determine different emission factors for stoves and central heating boilers from the values given in the cited literature. Thus for solid fuels the same proportions given from the dioxin EFs, and for oil the proportions of carbon black given in (HÜBNER et al. 1996), was used. For natural gas it was assumed that the values given in literature are valid for stoves and that the values for central heating boilers are assumed to be five times lower. Sup-plemental PAK emission factors for vaporizing burners, wood stoves and cooking stoves, natu-ral-draft wood boilers and pellet stoves are taken from the EMEP/EEA Air Pollutant Emission In-ventory Guidebook 2016. Inter alia for commercial and institutional plants the same emission factors as used for small (and medium) plants of category 1.A.2 were chosen (the share of the different size classes is based on expert judgement). The resulting PAH emissions for category 1.A.4.a.1, 1.A.4.b.1 and 1.A.4.c.1 were subdivided

into the contributing PAH4 substances Benzo(b)fluoranthene, Benzo(a)pyrene, Ben-zo(k)fluoranthene, Indeno(1,2,3-cd)pyrene considering the ratio of emission factors from the EMEP/EEA Air Pollutant Emission Inventory Guidebook 2019.

PCB emission factors for or wood stoves and cooking stoves, pellet stoves, natural-draft wood boilers, coal and gasoil are selected from the EMEP/EEA Air Pollutant Emission Inventory Guidebook 2016. The PCB emission factor of 3 600 µg/t for residual fuel oil has been selected from (KAKAREKA et al. 2004) and was converted to 85 µg/GJ. The PCB emission factors for other heating types burning biofuels and waste have been derived from the ratio of Dioxin and PCB emission factors according to the measurements undertaken by (HEDMAN et al. 2006). A ratio of 0.09 g PCB per g Dioxin has been selected. The same ratio has also been selected for refinery fuels. 1.A.4.c.1 Agriculture/Forestry/Fishing: stationary

For oil, gas and LPG the same emission factors as used for small (and medium) plants of cate-gory 1.A.2 were used (the share of the different size classes is based on expert judgement). Other emission factors are derived from category 1.A.4.a.1 assuming similar structure of heating types in both categories (implied emission factors). Those values given in the following tables are averaged values per fuel category.



Table 157: NFR 1.A.4. PCDD/F emission factors for the year 2018.

No. Heating type Fuel Emission factors PCDD/F [mg/TJ]

1.A.4.a 1.A.4.b 1.A.4.c

#1 Fuel oil boilers


0.002 0.0004

NO

NO NO NO

0.0015 NO NO


0.0015







0.0025 0.00069(1)

0.0025 NO


0.0016 0.00069(1)

0.0016 NO

#10 LPG stoves LPG and gas works gas 0.0030 0.0030

0.0025 #11 LPG boilers LPG and gas works

gas 0.0017 0.0025











#21 Coal stoves


NO

NO NO NO NO

0.75

0.75 0.75 0.75 NO

0.47(1)

#22 Coal boilers


NO

NO NO NO

0.30

0.38

0.38 0.38 0.38 NO




Table 158: NFR 1.A.4. HCB emission factors for the year 2018.

No. Heating type Fuel Emission factors HCB [mg/TJ]

1.A.4.a 1.A.4.b 1.A.4.c

#1 Fuel oil boilers


0.19 0.080

NO

NO NO NO

0.15 NO NO


0.15





Gas oil 0.12 0.15



0.14 0.078(1)

0.25 NO


0.14 0.078(1)

0.25 NO



#12 Wood stoves and cooking stoves Fuel wood Char coal 600 600

600 #13 Tiled wood stoves and masonry

heaters Fuel wood 600 600

#14 Mixed-fuel wood boilers Fuel wood NO 600

#15 Natural-draft wood boilers Fuel wood NO 160

#16 Forced-draft wood boilers Fuel wood NO 100

#17 Wood chips boilers with conventional technology Wood waste 240 240

81.93(1) #18 Wood chips boilers with oxygen sensor emission control Wood waste 160 160

#19 Pellet stoves Wood waste 100 100

#20 Pellet boilers Wood waste 30 30

#21 Coal stoves


NO

NO NO NO NO

600

600 600 600 NO

600

#22 Coal boilers


NO

NO NO NO 250

600

600 600 600 NO




Table 159: NFR 1.A.4. PAH4 emission factors for the year 2018.

No. Heating type Fuel Emission factors PAH4 [g/TJ]

1.A.4.a 1.A.4.b 1.A.4.c

#1 Fuel oil boilers


0.24 0.16 NO

NO NO NO

0.24 NO NO


0.24





Gas oil 0.040 0.040



0.040 0.0032

0.040 NO


0.010 0.0032

0.010 NO



#12 Wood stoves and cooking stoves Fuel wood 345 345

177.20(1)


Fuel wood Char coal 170 170

#14 Mixed-fuel wood boilers Fuel wood NO 85

#15 Natural-draft wood boilers Fuel wood NO 35


#17 Wood chips boilers with conventional technology Wood waste 24 24

85 #18 Wood chips boilers with oxygen sensor emission control Wood waste 2.0 2.0

#19 Pellet stoves Wood waste 35 35


#21 Coal stoves


NO

NO NO NO NO

170

170 170

24 NO

81.41(1)

#22 Coal boilers


NO

NO NO NO 26

85

85 85 12

NO




Table 160: NFR 1.A.4.a.1 share of total PAH4 emissions 2018.

No. Heating type PAH4 emission share [%] Benzo_a Benzo_b Benzo_k Indeno_k

#1 Fuel oil boilers 30.8% 34.6% 23.1% 11.5%

#2 Gas oil stoves 22.9% 11.4% 20.0% 45.7%

#3 Vapourizing burners 22.9% 11.4% 20.0% 45.7%

#4 Yellow burners 22.9% 11.4% 20.0% 45.7%


22.9% 11.4% 20.0% 45.7%


22.9% 11.4% 20.0% 45.7%

#7 Natural gas convectors 18.2% 27.3% 27.3% 27.3%

#8 Atmospheric burners 18.2% 27.3% 27.3% 27.3%

#9 Forced-draft natural gas burners 18.2% 27.3% 27.3% 27.3%

#10 LPG stoves 22.9% 11.4% 20.0% 45.7%

#11 LPG boilers 22.9% 11.4% 20.0% 45.7%

#12 Wood stoves and cooking stoves 35.1% 32.2% 12.2% 20.6%


28.6% 45.7% 14.3% 11.4%

#14 Mixed-fuel wood boilers NO NO NO NO

#15 Natural-draft wood boilers NO NO NO NO

#16 Forced-draft wood boilers NO NO NO NO


28.6% 45.7% 14.3% 11.4%


28.6% 45.7% 14.3% 11.4%

#19 Pellet stoves 28.6% 45.7% 14.3% 11.4%

#20 Pellet boilers 28.6% 45.7% 14.3% 11.4%

#21 Coal stoves NO NO NO NO

#22 Coal boilers 38.0% 35.2% 14.1% 12.7%




Table 161: NFR 1.A.4.b.1 share of total PAH4 emissions 2018.

No. Heating type PAH4 emission share [%] Benzo_a Benzo_b Benzo_k Indeno_k

#1 Fuel oil boilers NO NO NO NO

#2 Gas oil stoves 22.9% 11.4% 20.0% 45.7%

#3 Vapourizing burners 22.9% 11.4% 20.0% 45.7%

#4 Yellow burners 22.9% 11.4% 20.0% 45.7%


22.9% 11.4% 20.0% 45.7%


22.9% 11.4% 20.0% 45.7%

#7 Natural gas convectors 18.2% 27.3% 27.3% 27.3%

#8 Atmospheric burners 18.2% 27.3% 27.3% 27.3%

#9 Forced-draft natural gas burners 18.2% 27.3% 27.3% 27.3%

#10 LPG stoves 22.9% 11.4% 20.0% 45.7%

#11 LPG boilers 22.9% 11.4% 20.0% 45.7%

#12 Wood stoves and cooking stoves 35.1% 32.2% 12.2% 20.6%


28.6% 45.7% 14.3% 11.4%

#14 Mixed-fuel wood boilers 35.1% 32.2% 12.2% 20.6%

#15 Natural-draft wood boilers 35.1% 32.2% 12.2% 20.6%

#16 Forced-draft wood boilers 9.8% 15.7% 4.9% 69.6%


35.1% 32.2% 12.2% 20.6%


28.6% 45.7% 14.3% 11.4%

#19 Pellet stoves 28.6% 45.7% 14.3% 11.4%

#20 Pellet boilers 28.6% 45.7% 14.3% 11.4%

#21 Coal stoves 27.2% 43.5% 16.3% 13.0%

#22 Coal boilers 38.0% 35.2% 14.1% 12.7%




Table 162: NFR 1.A.4. PCB emission factors for the year 2018.

No. Heating type Fuel Emission factors PCB [mg/TJ]

1.A.4.a 1.A.4.b 1.A.4.c

#1 Fuel oil boilers


NA NA NO

NO NO NO

NA NO NO

#2 Gas oil stoves Gas oil NA NA

NA

#3 Vapourizing burners Gas oil NA NA

#4 Yellow burners Gas oil NA NA

#5 Blue burners with conventional technology Gas oil NA NA


Gas oil NA NA

#7 Natural gas convectors Natural gas NA NA

NA #8 Atmospheric burners Natural gas Biogas and landfill gas

NA NA

NA NO


NA NA

NA NO

#10 LPG stoves LPG and gas works gas NA NA NA

#11 LPG boilers LPG and gas works gas NA NA











#21 Coal stoves


NO

NO NO NO NO

170

170 170 170 NO

170

#22 Coal boilers


NO

NO NO NO

0.027

170

170 170 170 NO





1.A.4.a.1 Commercial/Institutional: stationary and 1.A.4.b.1 Residential: stationary

As already described in chapter 1.4 the emission inventories of PM for different years were pre-pared by contractors and incorporated into the inventory system afterwards (WINIWARTER et al. 2001).

For categories 1.A.4.a.1 and 1.A.4.b.1 additional PM emission factors were taken from the EMEP/EEA Air Pollutant Emission Inventory Guidebook 2016, the Fact Sheet of the Swiss Fed-eral Office for the Environment (FOEN 2015), (GERMAN ENVIRONMENT AGENCY 2008) and (UMWELTBUNDESAMT 2006a) based on literature research (UMWELTBUNDESAMT 2017c) to reflect the twenty-two technology and fuel dependent main sub categories (heating types). The shares of PM10 (90%) and PM2.5 (80%) were also taken from (WINIWARTER et al. 2001).

Mixed-fuel wood boilers stock with (comparatively) advanced technology is considered with (slightly) lower PM emissions than conventional equipment. The biomass share is given in Table 144.

Table 163: PM emission factors of category 1.A.4 advanced mixed-fuel wood boilers (Source: EMEP/EEA Air Pollutant Emission Inventory Guidebook 2016).

Fuel No. PM [kg/TJ]

1.A.4.a/b

Fuel wood #14 100.0

The PM emission estimates for categories 1.A.4.a.1 and 1.A.4.b.1 in general do not provide in-formation whether the condensable component is included or excluded. Only a few emission fac-tors explicitly include or exclude the condensable fraction (see also chapter 12.3).

1.A.4.c.1 Agriculture/Forestry/Fishing: stationary

All emission factors are derived from category 1.A.4.a.1 assuming similar structure of heating types in both categories (implied emission factors). Those values given in the following table are averaged values per fuel category.

The PM emission estimates for category 1.A.4.c.1 in general do not provide information whether the condensable component is included or excluded. Only a few emission factors explicitly include or exclude the condensable fraction (see also chapter 12.3).



Table 164: NFR 1.A.4. PM emission factors for the year 2018.

No. Heating type Fuel Conden-sable fraction

Emission factors PM [kg/TJ]

1.A.4.a 1.A.4.b 1.A.4.c

#1 Fuel oil boilers

Residual fuel oil84 Diesel85 Petroleum, other petroleum products

unknown unknown NO

6.67 50

NO

NO NO NO

6.67 NO NO

#2 Gas oil stoves Gas oil86 unknown 3.0 3.0

2.25 (1)

#3 Vapourizing burners Gas oil86 unknown 3.0 3.0

#4 Yellow burners Gas oil86 unknown 3.0 3.0


Gas oil87 excluded 2.0 2.0

#6

Blue burners with low temperature or condensing technology

Gas oil87 excluded 1.5 1.5

#7 Natural gas convectors Natural gas88 excluded 2.20 2.20

0.72(1) #8 Atmospheric burners

Natural gas86 Biogas and landfill gas86

unknown unknown

0.50 0.50

0.50 NO

#9 Forced-draft natural gas burners

Natural gas89 Biogas and landfill gas89

unknown unknown

0.20 0.20

0.20 NO

#10 LPG stoves LPG and gas works gas90

unknown

2.20

2.20

1.64(1) #11 LPG boilers LPG and gas works

gas86 unknown

0.50

0.50

#12 Wood stoves and cooking stoves

Fuel wood91 Char coal91 included 148 148

101.98(1) #13 Tiled wood stoves and

masonry heaters Fuel wood92 unknown 100 100

#14 Mixed-fuel wood boilers Fuel wood93 included NO 122.1

#15 Natural-draft wood boilers Fuel wood94 excluded NO 75

84 EMEP/EEA Guidebook 2016, Table 3-30 Non-residential sources, medium-sized (> 50 kWth to ≤ 1 MWth) boilers

liquid fuels 85 For diesel a value similar to locomotive diesel engines has been selected 86 WINIWARTER et al. (2001) 87 EMEP/EEA Guidebook 2016, Table 3-21 Boilers burning liquid fuels 88 EMEP/EEA Guidebook 2016, Table 3-13 Fireplaces burning natural gas 89 EMEP/EEA Guidebook 2016, Table 3-19 Boilers burning natural gas 90 EMEP/EEA Guidebook 2016, Table 3-20 Stoves burning liquid fuels 91 WINIWARTER et al. (2007): The condensable fraction was considered, if data options were available. 92 FOEN (2015) 93 EMEP/EEA Guidebook 2016, Table 3-24 Advanced / ecolabelled stoves and boilers burning wood 94 EMEP/EEA Guidebook 2016, Table 3-34 Non-residential sources, manual boilers burning wood



No. Heating type Fuel Conden-sable fraction

Emission factors PM [kg/TJ]

1.A.4.a 1.A.4.b 1.A.4.c

#16 Forced-draft wood boilers Fuel wood92 unknown NO 50


Wood waste92 unknown 100 100

33.82(1) #18 Wood chips boilers with oxygen sensor emission control

Wood waste91 included 55 55

#19 Pellet stoves Wood waste91 included 30 30

#20 Pellet boilers Wood waste95 unknown 19 19

#21 Coal stoves

Hard coal and hard coal briquettes86 Lignite and brown coal86 Brown coal briquettes86 Coke86 Peat86

unknown unknown unknown unknown unknown

NO

NO

NO NO NO

153

153

153 153 NO

107.56(1)

#22 Coal boilers

Hard coal and hard coal briquettes86 Lignite and brown coal86 Brown coal briquettes86 Coke86 Industrial waste86

unknown unknown unknown unknown unknown

NO

NO

NO NO 55

94

94

94 94

NO


Other sources of PM emissions

For the following sources it is assumed that particle sizes are equal or smaller than PM2.5.

Barbecue

For activity data 11 kt of char coal has been calculated (WINIWARTER et al. 2007) from foreign trade statistics and production data (Import 11 900 t, Export 1 900 t, Production 1 000 t). An emission factor of 2 237 g TSP/GJ char coal has been selected which is 69 347 g/t char coal assuming a calorific value of 31 GJ/t. This leads to 763 t PM/year for the whole time series. It has to be noted that, for reasons of time series consistency, constant activity data has been se-lected for the whole time series which is slightly different to actual energy statistics. However, because of the relatively high uncertainty of energy statistics regarding the trend in char coal consumption (validation not possible at current) and the high uncertainty of PM estimates from this source it has been chosen to keep this approach.

95 GERMAN ENVIRONMENT AGENCY (2008)



Bonfire

It is assumed that one bonfire is sparked every year for each 5 000 rural inhabitants. This leads to 1 000 bonfires each year for all 5 Mio rural inhabitants. The average size of a fire is estimated to have 30 m³ of wood which is 10 m³ of solid wood. Assuming a heating value of 10 GJ/m³ wood and selecting an emission factor of 1 500 g/GJ (similar to open fire places, expert guess from literature) this leads to 150 kg PM for each fire and 150 t PM for each year.

Open fire pits

It is assumed that one open fire pit exists for each 2 500 inhabitants. Assuming 20 fires per year and fire pit this leads to 66 400 fires each year. Assuming 0.025 m³ of solid wood per fire which is 0.3 GJ and selecting an emission factor of 800 g/GJ (open fireplace, EPA 1999, KLIMONT et al. 2002) this leads to 240 g PM/fire and 16 t PM for each year.


Updates of activity data and of NCVs follow the updates of the IEA-compliant energy balance compiled by the federal statistics authority Statistik Austria).

Changes according to revision of energy demand model for space heating

The module ‘Heating type by technology’ was updated with a new approach considering recent market data and expert consultation (on sales by fuel technology). This information was used for remodelling the heating stock and turnover based on two studies (E7 ENERGIE MARKT ANALYSE GMBH 2009, 2017) resulting in revised percentual consumption by type of heating (see Table 132 to Table 134, Table 136 to Table 138).

Additionally, the mixed-fuel wood boiler stock was subdivided into two categories (advanced and conventional, see Table 143). Advanced technology is considered with (slightly) lower NOx, CO, NMVOC, CH4 and PM emissions than conventional equipment.



3.2 NFR 1.A Mobile Fuel Combustion Activities

3.2.1 General description

In this chapter the methodology for estimating emissions of mobile sources in NFR 1.A.3, transport and NRMM (Non-Road Mobile Machinery) of NFR 1.A.2.g, NFR 1.A.4 and NFR 1.A.5, is described.

NFR Category 1.A.3 Transport comprises emissions from fuel combustion, gasoline evapora-tion, abrasion of brake and tyre wear and dust dispersion of dust by road traffic in the subcate-gories.

Table 165: NFR and SNAP categories of 1.A Mobile Fuel Combustion Activities.

Activity NFR Category SNAP

NFR 1.A.2 Manufacturing Industry and Combustion

Industry, Mobile Machinery NFR 1.A.2.g.vii

0808 Other Mobile Sources and Machinery-Industry

NFR 1.A.3 Transport

Civil Aviation NFR 1.A.3.a

Civil Aviation NFR 1.A.3.a 0805

Civil Aviation (Domestic, LTO)

NFR 1.A.3.a.2 080501 Domestic airport traffic (LTO cycles < 1 000 m)

International Aviation (LTO)

NFR 1.A.3.a.1 080502 International airport traffic (LTO cycles < 1 000 m)

Road Transportation NFR 1.A.3.b

R.T., Passenger cars NFR 1.A.3.b.1 0701 Passenger cars

R.T., Light duty vehicles NFR 1.A.3.b.2 0702 Light duty vehicles < 3.5 t

R.T., Heavy duty vehicles NFR 1.A.3.b.3 0703 Heavy duty vehicles > 3.5 t and buses

R.T., Mopeds & Motorcycles NFR 1.A.3.b.4 0704 Mopeds and Motorcycles < 50 cm³

0705 Motorcycles > 50 cm3

Gasoline evaporation from vehicles

NFR 1.A.3.b.5 0706 Gasoline evaporation from vehicles

Automobile tyre and brake wear NFR 1.A.3.b.6 0707 Automobile tyre and brake wear

Automobile road abrasion NFR 1.A.3.b.7 0707 Automobile road abrasion

Railways NFR 1.A.3.c 0802 Other Mobile Sources and Machinery-Railways

Navigation NFR 1.A.3.d 0803 Other Mobile Sources and Machinery-Inland waterways

0804 Other Mobile Sources and Machinery-Maritime activities

Other transportation NFR 1.A.3.e 0810 Pipelines compressors and other transportation

NFR 1.A.4 Other Sectors

Residential 1.A.4.b.2 0809 Other Mobile Sources and Machinery-Household and gardening



Activity NFR Category SNAP

Agriculture/ Forestry/ Fisheries 1.A.4.c.2 0806 Other Mobile Sources and Machinery-Agriculture

0807 Other Mobile Sources and Machinery-Forestry

NFR 1.A.5 Other 1.A.5.b 0801 Other Mobile Sources and

Machinery-Military

Memo Items

Civil Aviation (Domestic, cruise) Mem 1.A.3.a.2 080503 Domestic cruise traffic (> 1 000 m)

International aviation (cruise) Mem 1.A.3.a.1 080504 International cruise traffic (> 1 000 m)

3.2.1.1 Completeness

Table 161 provides information on the status of emission estimates of all sub categories. A “” indicates that emissions from this sub category have been estimated. Table 160 provides an overview about NFR categories and the corresponding SNAP codes.

Table 166: Completeness of 1.A Mobile Fuel Combustion Activities.

NFR Category

NO

x

CO

NM

VOC

SOx

NH

3

TSP

PM10

PM2.

5

Pb

Cd

Hg

DIO

X

PAH

HC

B

PCB

1.A.2.g.7 Industry, Mobile Machinery

1.A.3.a Civil Aviation – LTO NE NE NE NE

1.A.3.b Road Trans- portation

1.A.3.c Railways 1.A.3.d Navigation 1.A.3.e Other

transportation NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO

1.A.4.b.2 Residential: Household and gardening (mo-bile)

1.A.4.c.2 Agriculture/ For-estry/Fishing: Off-road Vehicles and Other Machinery

1.A.5.b Other, Mobile (Including military)

Mem.1.A.3.a.Civil Avia-tion – Cruise NE NE NE NE

Mem.1.A.3.d International maritime Navigation NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO



3.2.2 Key Categories

Key category analysis is presented in Chapter 1.5. This chapter includes information on the transport sector. Key sources within this category are presented in Table 162.

Table 167: Key sources of sector Transport.

NFR Category Category Name

Key Categories pollutant KS Assessment

1.A.3.b.1 R.T., Passenger cars NOx, NMVOC, CO, Pb1), TSP1), PM10, PM2.5

LA, TA

1.A.3.b.2 R.T., Light duty vehicles NOx, PM10, PM2.5

LA, TA

1.A.3.b.3 R.T., Heavy duty vehicles NOx, PAH1) TSP1), PM101), PM2.5 LA, TA

1.A.3.b.4 R.T., Mopeds & Motorcycles NMVOC, CO LA, TA 1.A.3.b.5 R.T., Gasoline evaporation NMVOC TA


Cd, TSP, PM10, PM2.5 LA, TA


TSP, PM10, PM2.5 LA, TA

1.A.3.c Railways TSP, PM10 LA LA = Level Assessment (if not further specified – for the years 1990 and 2017) TA = Trend Assessment 2016 Note: 1)only TA, 2)only LA

3.2.3 Uncertainty Assessment The following chapter provides a quantitative estimate of uncertainties with respect to NOx, NH3, NMVOC, SO2 and PM2.5 emissions from Mobile Fuel Combustion Activities. In general the method applied for the assessment of uncertainty is according to the EMEP/EEA air pollutant emission inventory guidebook 2016 (EEA 2016), using an average of the default values, based on the definitions of the qualitative ratings (see Chapter 1.7 and Table 25). For estimating the uncertainty of the emission factors of NMVOC, PM2.5 and NH3 for sector 1.A.3.b. Road Transport, experts from TU Graz have been consulted. For NMVOC, cold start and aged gaso-line vehicles are very uncertain (rating level C – 125%); for PM2.5 lies the uncertainty before all in the non-exhaust emissions (rating level C – 125%); for NH3 the rating level 3 (200%) has been suggested.

Table 168: Uncertainties for activity data, emission factors and combined uncertainties.

Sector Pollutant Uncertainty Activity Data

[%]

Uncertainty Emission

Factor

[%]

Combined uncertainties

[%]

1.A.3.a Civil Aviation – LTO

SO2 3.0 20.0 20.22 NOx 3.0 40.0 40.11

NMVOC 3.0 40.0 40.11 NH3 3.0 125.0 125.04

PM2.5 3.0 40.0 40.11



Sector Pollutant Uncertainty Activity Data

[%]

Uncertainty Emission

Factor

[%]

Combined uncertainties

[%]

1.A.3.b Road Transportation

SO2 3.1 20.0 20.24 NOx 3.1 40.0 40.12

NMVOC 3.1 125.0 125.04 NH3 3.1 200.0 200.02

PM2.5 3.1 125.0 125.04

1.A.3.c Railways

SO2 3.0 20.0 20.22 NOx 3.0 40.0 40.11

NMVOC 3.0 40.0 40.11 NH3 3.0 125.0 125.04

PM2.5 3.0 40.0 40.11

1.A.3.d Navigation

SO2 3.0 20.0 20.22 NOx 3.0 40.0 40.11

NMVOC 3.0 40.0 40.11 NH3 3.0 125.0 125.04

PM2.5 3.0 40.0 40.11

1.A.3.e Other transportation

SO2 2.0 125.0 125.02 NOx 2.0 10.0 10.20

NMVOC 2.0 200.0 200.01 NH3 2.0 750.0 750.00

PM2.5 2.0 125.0 125.02

3.2.4 NFR 1.A.3.a Civil Aviation – LTO

The category 1.A.3.a Civil Aviation-LTO contains flights according to Visual Flight Rules (VFR) and Instrument Flight Rules (IFR) for domestic aviation (national LTO – landing/take off) and for international aviation (international LTO – landing/take off). Domestic cruise and international cruise is considered under Memo Item 1.A.3.a Civil Aviation – Cruise. Military Aviation is allo-cated to 1.A.5 Other.

Methodological Issues

IFR – Instrument Flight Rules

For the years 1990–1999 a country-specific methodology was applied. The calculations are based on a study commissioned by the Umweltbundesamt finished in 2002 (KALIVODA/KUDRNA 2002). This methodology is consistent with the very detailed IPCC 2006 GL Tier 3B methodolo-gy (advanced version based on the MEET model (KALIVODA/KUDRNA 1997): air traffic movement data96 (flight distance and destination per aircraft type) and aircraft/engine performances data were used for the calculation.

For the years from 2000 onwards the IPCC 2006 GL Tier 3A methodology has been applied. Tier 3A takes into account average fuel consumption and emission data for LTO phases and various flight lengths, for an array of representative aircraft categories.

96 This data is also used for the split between domestic and international aviation.



VFR – Visual Flight Rules

The EMEP/EEA 2016 (EEA 2016) simple methodology (Tier 1, fuel-based methodology) is ap-plied.

Activity Data

Fuel consumption (kerosene and gasoline) for 1.A.3.a Civil Aviation – LTO is presented below.

Table 169: Activities for 1.A.3.a.ii Civil Aviation – LTO: 1990–2018.

Year Activity dom. LTO dom. LTO int. LTO

Kerosene [TJ] Gasoline [TJ] Kerosene [TJ]

1990 137 103 1,241

1991 148 106 1,417

1992 159 109 1,593

1993 170 113 1,769

1994 181 116 1,945

1995 192 93 2,121

1996 222 89 2,266

1997 252 100 2,412

1998 283 108 2,557

1999 290 115 2,614

2000 265 84 2,890

2001 217 77 2,743

2002 226 99 3,207

2003 221 107 3,342

2004 237 99 3,987

2005 225 115 3,714

2006 269 119 3,680

2007 274 118 3,979

2008 305 121 4,044

2009 280 135 3,700

2010 267 121 3,794

2011 231 182 4,314

2012 232 105 4,147

2013 232 108 4,035

2014 211 99 4,080

2015 205 111 4,309

2016 203 135 4,406

2017 189 98 4,267

2018 221 95 4,639

1990–2018 61% -8% 274%



IFR flights

For the years 1990–1999 fuel consumptions for the different transport modes IFR national LTO, IFR international LTO, IFR national cruise and IFR international cruise as obtained from the MEET model (KALIVODA & KUDRNA 1997) were summed up to a total fuel consumption figure. This value was compared with the total amount of kerosene sold in Austria of the national ener-gy balance. As „fuel sold” is a robust value, the fuel consumption of IFR international cruise was adjusted so that the total fuel consumption of the calculations according to the MEET model is consistent with national fuel sales figures from the energy balance. The reason for choosing IFR international cruise for this adjustment is that this mode is assumed to have the highest uncer-tainty.

For the years from 2000 onwards fuel consumption for the different transport modes IFR na-tional LTO, IFR international LTO, IFR national cruise and IFR international cruise was calculat-ed according to the IPCC 2006 GL Tier 3A method, with average consumption data per aircraft types and flight distances. The fuel consumption of IFR international cruise was adjusted as ex-plained above.

Bottom up Methodology – fuel consumed

Based on the number of flight movements per aircraft type and airport (national and internation-al) departing Austria, the distances for each airport pair and the specific fuel consumption per aircraft type and distance class, FC (kerosene) and emissions are calculated bottom up. Up to the submission 2017 flight movements were obtained from special analyses by Statistik Austria (STATISTIK AUSTRIA 200897, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016). In addition, do-mestic flight movements were compared with a second data source for flight movements, Aus-trocontrol (AUSTRO CONTROL 200798, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018). Since the submission 2018 flight movements are only taken from Austrocontrol, as they seem to be more representative compared with international data.

Up to the submission 2017 the distances between airport pairs have been extracted based on IATA codes from single queries on the internet.99 This approach has been changed in the sub-mission 2018, as an automatic distance generator has been applied in the calculation model based on the great circle distance:

e = r · arccos(sin(φA) · sin(φB) + cos(φA) · cos(φB) · cos(λB – λA))

A…departure aerodrome B…arrival aerodrome

Each aerodrome being reported in the flight movements needs to be integrated in the calcula-tion model with its geographical degree of latitude and longitude.

Top down Methodology – fuel sold

The calculated bottom up result for total kerosene consumption has always been and is still be-ing compared to the total fuel sold reported by the national energy balance (IEA 2017). If the bottom up approach underestimates fuel sold, the delta has been fully allocated to international cruise, as the domestic flight movements had already been increased in line with Austrocontrol data. From the submission 2018 onwards any delta between the bottom up result and the offi-cial amount of kerosene sold is being allocated to domestic LTO, international LTO, national cruise and international cruise depending on their relative shares in total kerosene consumption.

97 for the years 2000–2007 98 for the years 2000–2006 99 www.world-airport-codes.com

http://www.world-airport-codes.com/



VFR flights Fuel consumption for VFR flights were directly obtained from the energy balance, as total fuel consumption for this flight mode is represented by the total amount of aviation gasoline sold in Austria.

The following table shows activity data and the numbers of national LTOs (IFR) which were ob-tained from the MEET Model (KALIVODA & KUDRNA 1997) for the years 1990–1999. Numbers of flight movements from 2000 onwards are taken from Statistik Austria, and for the year 2016 and onwards from Austrocontrol.

Table 170: Fuel consumption for VFR and IFR flights and number of IFR LTO cycles: 1990–2018.

Year Activity

VFR Gasoline

[kt]

nat. LTO IFR Kerosene [kt]

nat. LTO IFR [flight mvts]

int. LTO Kerosene [kt]

int. LTO IFR [flight mvts]

1990 2.49 3.16 6,220 28.65 41,689

1991 2.56 3.42 6,644 32.71 41,689

1992 2.64 3.67 7,450 36.77 48,574

1993 2.72 3.92 7,947 40.83 55,459

1994 2.81 4.18 8,219 44.90 62,344

1995 2.24 4.43 8,923 48.96 69,230

1996 2.15 5.13 10,233 52.31 76,115

1997 2.42 5.83 11,013 55.67 81,721

1998 2.60 6.53 12,025 59.03 87,327

1999 2.77 6.70 12,210 60.34 92,933

2000 2.04 6.11 22,611 66.71 95,033

2001 1.87 5.01 20,325 63.33 97,740

2002 2.39 5.21 21,422 74.04 95,961

2003 2.60 5.10 20,243 77.15 97,873

2004 2.41 5.47 20,175 92.03 110,470

2005 2.79 5.20 20,179 85.74 117,837

2006 2.87 6.20 20,727 84.94 120,757

2007 2.86 6.33 20,740 91.85 129,737

2008 2.94 7.04 21,457 93.35 132,466

2009 3.27 6.46 20,530 85.41 120,723

2010 2.92 6.16 20,532 87.57 123,759

2011 4.40 5.32 16,185 99.58 140,058

2012 2.54 5.37 16,405 95.73 135,691

2013 2.61 5.35 15,741 93.14 129,500

2014 2.38 4.87 14,776 94.11 130,674

2015 2.65 4.73 13,282 99.39 129,921

2016 3.28 4.70 15,515 101.76 151,241

2017 2.39 4.37 14,781 98.55 145,143

2018 2.30 5.11 19,735 107.15 157,722

1990–2018 -8% 62% 217% 274% 278%



Emission Factors

IFR flights

The EFs from the old CORINAIR Guidebook have been used for the years 2000–2015 and will not be changed any more as they represent the state of the art of aircrafts for those years. In contrast to road transport, where EFs are differentiated by age and technology of the vehicle, this is not the case in aviation.

As in reality there are always flight movements with aircrafts which are not listed in the spread-sheet, an allocation of unknown aircrafts to listed aircrafts in the spreadsheet has to be under-taken based on research about engine type, number of engines, production series etc. If the unknown aircraft cannot be allocated, it is being labelled as UNKNOWN. The specific fuel con-sumption and emission factors are separately calculated on the basis of the national and inter-national LTO and cruise averages of each year. This means the calculation distinguishes be-tween: Unknown aircraft type for national flights – LTO Unknown aircraft type for national flights – cruise Unknown aircraft type for international flights – LTO Unknown aircraft type for international flights – cruise For LTOunknown the equation is:

FC/LTO = Sum FC_LTOunknown / Sum flights movementsunknown

For Cruiseunknown the equation is:

FC/km = (Sum FC_cruiseunknown / sum nm cruiseunknown) * 125

125 nm (nautical miles) is the shortest distance class. For the other distance classes >125 nm the values are being extrapolated.

SO2

For the years 1990–1999 SO2 emissions were taken from the national aviation study commis-sioned by Umweltbundesamt (KALIVODA & KUDRNA 2002).

For the years 2000–2015 SO2 emissions have been calculated with an EF from the CORINAIR Guidebook (1kg/t fuel for LTO and cruise).

For the years from 2016 onwards EFs from Annex 5 of the EMEP/EEA 2016 Guidebook per air-craft type and distance class are applied.

NOx, CO

For the years 1990–1999 emission estimates for fuel consumption, NOx and CO were taken from an aviation study commissioned by Umweltbundesamt (KALIVODA & KUDRNA 2002) and the emission factors are aircraft/engine specific.

For the years 2000–2015 EFs from CORINAIR Tier 3A were applied. Tier 3A takes into account average fuel consumption and emission data for LTO phases and various flight lengths, for an array of representative aircraft categories.

For the years from 2016 onwards EFs from Annex 5 of the EMEP/EEA 2016 Guidebook per air-craft type and distance class are applied.



NMVOC

For the years 1990–1999 NMVOC emissions for IFR flights have been calculated like NOx (VOC emissions calculated with a country specific method where the percentile rate share of NMVOC from total HC emission was calculated. (KALIVODA & KUDRNA 2002).

For the years 2000–2015 NMVOC emissions for IFR flights have been calculated in this way: Total VOC_HC emissions have been calculated with the implied emission factor for the year 1999 as obtained from the national aviation study (KALIVODA & KUDRNA 2002) and deducted by CH4 emissions.

For the years from 2016 onwards total HC emissions have been calculated applying the EFs from Annex 5 of the EMEP/EEA 2016 Guidebook (per aircraft type and distance class) and de-ducted by CH4 emissions to estimate NMVOC emissions.

NH3

For the years 1990–1999 NH3 emissions for IFR flights have been calculated like NOx (KALIVODA & KUDRNA 2002).

For the years from 2000 onwards NH3 emissions for IFR flights have been calculated with an IEF from the year 2000 obtained from the study mentioned above (KALIVODA & KUDRNA 2002).

No NH3 EFs are included in Annex 5 of the EMEP/EEA 2016 Guidebook per aircraft type and distance class.

PM2.5

For the years 1990–1999 emission estimates were taken from the national aviation study (KALIVODA & KUDRNA 2002).

For the years from 2000 onwards PM2.5 emissions for IFR flights have been calculated with an IEF from the year 2000 obtained from the study mentioned above (KALIVODA & KUDRNA 2002).

VFR flights

For the years 1990–1999 emission estimates were taken from the national aviation study (KALIVODA & KUDRNA 2002).

From the submission 2018 onwards, for the years from 2000 onwards SO2, NOx, NMVOC and CO emissions of VFR flights have been calculated with EFs according to the EMEP/EEA 2016 Guidebook (Tier 1). NH3, PM2.5 and VOC_HC emissions are still being calculated with the IEFs of the year 2000 taken from (KALIVODA & KUDRNA 2002).

Table 171: Tier 1 EF according to the EMEP/EEA GB 2016

EFs (EMEP/EEA 2016, Tier 1) [kg/t fuel]

SOx 1.0

NOx 4.0

NMVOC 19.0

CO 1200.0



Table 172: IEF for the year 2000 according to (KALIVODA & KUDRNA 2002)

IEF (Kalivoda & Kudrna 2002) 2000 [t] [kg/t fuel]

Fuel 2 039

NH3 0.06 0.03

PM2.5 0.03 0.14

VOC_HC 38 18.87

In the following tables the IEFs for 1.A.3.a. Civil Aviation (domestic LTO + international LTO) are presented. The jump from 2015 to 2016 for all gases except NH3 and PM2.5 is due to the changed activity data and emission factors which were being used for calculating IFR flights from the year 2016 onwards.

Table 173: Activities and Implied emission factors for NEC gases for 1.A.3.a.ii Civil Aviation (domestic LTO + international LTO): 1990–2018.

Year Activity IEF SO2 IEF NOx IEF NMVOC IEF NH3 IEF PM2.5 [TJ] [t/PJ]

1990 1,481 22.2 275.5 137.8 0.20 23.5

1991 1,671 22.3 276.8 128.4 0.19 23.6

1992 1,861 22.3 277.9 121.0 0.19 23.7

1993 2,051 22.4 278.8 115.0 0.19 23.8

1994 2,242 22.4 279.4 110.0 0.19 23.9

1995 2,405 22.6 282.3 101.9 0.18 24.2

1996 2,577 22.6 282.5 110.7 0.18 24.3

1997 2,764 22.6 281.7 120.1 0.18 24.2

1998 2,948 22.6 281.1 128.0 0.18 24.2

1999 3,018 22.6 284.3 125.0 0.18 24.2

2000 3,239 23.1 266.9 116.4 0.17 24.4

2001 3,038 23.1 265.9 115.5 0.17 24.5

2002 3,532 23.1 285.0 115.8 0.17 24.4

2003 3,670 23.1 286.8 116.0 0.17 24.4

2004 4,323 23.1 291.6 113.4 0.17 24.5

2005 4,055 23.1 270.2 115.4 0.17 24.4

2006 4,067 23.1 263.8 116.4 0.17 24.4

2007 4,372 23.1 267.8 115.4 0.17 24.4

2008 4,470 23.1 267.0 115.8 0.17 24.4

2009 4,115 23.1 270.2 117.8 0.18 24.3

2010 4,181 23.1 272.9 116.1 0.17 24.4

2011 4,726 23.1 272.3 118.5 0.18 24.2




2012 4,484 23.1 275.8 113.4 0.17 24.5

2013 4,375 23.1 283.8 113.9 0.17 24.5

2014 4,390 23.1 290.6 112.7 0.17 24.5

2015 4,624 23.1 295.9 112.9 0.17 24.5

2016 4,744 19.5 317.3 45.4 0.17 24.4

2017 4,555 19.5 324.2 40.9 0.17 24.5

2018 4,955 19.5 326.7 41.7 0.17 24.6

Emission factors for heavy metals are presented in chapter 3.2.8.

Category-specific Quality Assurance and Quality Control (QA/QC)

The following QA/QC activities on time series consistency, completeness and comparison with international dataset were done first for CO2 and in response to the UNFCCC review. However, the methodological changes are also relevant for the calculation of the air pollutants which are therefore described as well in the following.



Time series consistency (Example for CO2)

Figure 38: Activity data from 1.A.3.a domestic Civil Aviation: 1990–2018.

Tier 3B (1990‒1999) & Tier 3A (2000‒2015)

From 1999 onwards a different methodology of emissions estimation has been applied for IFR flights. For the years 1990–1999 a country-specific methodology (consistent with the IPCC 2006 GL Tier 3B methodology), for the years from 2000 onwards the Tier 3A methodology was ap-plied.

To show that there is no underestimation of domestic aviation emissions, domestic fuel con-sumption is multiplied with the default CO2 emission factor of 3 150 kg CO2/Mg fuel (CORINAIR, KALIVODA & KUDRNA 2002). Total reported CO2 emissions for domestic aviation in the year 2000 are consistent with the IPCC 2006 GL Tier 3A methodology (new method), whereas the Tier 3B methodology (old method) deviates by 22%.

Table 174: Methodology dependent calculation of CO2 emissions from 1.A.3.a Civil Aviation in 2000.

2000

dom LTO dom. LTO dom. cruise dom. deviation gasoline kerosene total

CO2 [kt] %

OLI2016 (1990–2015) 6.4 19.3 41.6 67.24

CORINAIR CO2 default EF Tier 3B methodology 6.4 21.6 54.1 82.11 22.1

CORINAIR CO2 default EF Tier 3A methodology 6.4 19.2 41.5 67.18 -0.1

0

50

100

150

200

250

300

350

400

45019

9019

9119

9219

9319

9419

9519

9619

9719

9819

9920

0020

0120

0220

0320

0420

0520

0620

0720

0820

0920

1020

1120

1220

1320

1420

1520

1620

1720

18

Activ

ity (T

J)

Domestic Civil Aviation 1.A.3.a




Since there is no systematic deviation between the two models’ results, Austria has decided not to replace the more accurate data applied for the period 1990–1999 (FCCC/ARR/2011/AUT§46).

The peak of activity data and GHG emissions in 1999, followed by a decrease within two years by nearly 30% is an artefact due to the shortcomings of the method used from 1999 onwards. The old methodology reflects much better real-world effects, because this methodology is con-sistent with the very detailed IPCC 2006 GL Tier 3B methodology (advanced version based on MEET (KALIVODA & KUDRNA 1997): air traffic movement data (flight distance and destination per aircraft type) and aircraft/engine performances data were used for the calculation. Due to budg-etary constraints such a detailed study has not been repeated since then.

Tier 3A updated (from submission 2018 onwards)

For the years 2000–2015 the Tier 3A methodology is used for IFR flights. Tier 3A is also used for calculating the year 2016, however with an improved set of flight movements and updated emission factors.

For the validation of the accuracy of the new data the year 2015 has been calculated within 2 steps:

In a first step (validation 1), for the validation of the updated calculation tool, the results for the year 2015 of the submission 2017 with the old aircraft types and emission factors was com-pared with the results when the same activity data is being calculated with the new set of avail-able aircraft types and emission factors.

Figure 39: Deviation of emissions of 1.A.3.a Civil Aviation ‒ Validation 1.

The new results for all aircraft types (known and unknown) are lower compared to the submis-sion 2017. It must be noted that many aircrafts which were unknown so far and for which aver-age EFs were calculated can now be allocated to aircraft types listed in the new emission fac-tors spreadsheet. Vice versa some aircraft types which were listed in the old spreadsheets are not listed any more in the new emission factor spreadsheet.

NOx_LTO NOx_Cruise HC_LTO HC_Cruise CO_LTO CO_Cruise SOx_LTO SOx_Cruis

eDomestic -3,9% -30,6% -88,6% -65,7% -40,7% -11,2% -21,3% -37,2%International 0,6% 14,4% -73,2% -58,9% -54,0% 56,3% -21,6% -15,8%

-100,0%

-75,0%

-50,0%

-25,0%

0,0%

25,0%

50,0%

75,0%

[%]

Deviation of 1.A.3.a IFR LTO Validation 1 compared to submission 2017


NOx_LTO NOx_Cruise HC_LTO HC_Cruise CO_LTO CO_Cruise SOx_LTO SOx_Cruise



For this reason, a comparison of FC and emissions between known aircraft types of the sub-mission 2018 and the previous submission with activity data from the submission 2017 is shown below to demonstrate the separated effect of the changed EFs. Especially HC and CO emis-sions have drastically changed, however resulting in very small shares (0.1 – 0.3%) compared to the previous submission.

Figure 40: Comparison of FC and emissions of known aircraft types.

An analysis of domestic flight movements in the year 2015 has shown that the following three aircraft types hold the strongest shares in flown distances holding together a share of 85%: Dash 8 Q400 4580 hp (DH8D) with 60% Fokker 100 (F100) incl. F70100 with 25%

This information is useful for the explanation of the changes in domestic emissions:

Table 175: Deviations in EFs of aircraft types DH8D and F100.

DOMESTIC Deviation Deviaton in EFs

DH8D F100

NOx_LTO -4% -0.1% -6%

NOx Cruise -31% -37% on weighted average for distance classes 250nm and 500nm

+5% on weighted average for distance classes 250nm and 500nm

HC_LTO -98% As IEFs have been used up to the submission 2018, an EF comparison on aircraft level is not possible.

HC_Cruise -66%

CO_LTO -41% +10% -49%

CO_Cruise -11% -50% on weighted average for distance classes 250nm and 500nm

+118% on weighted average for distance classes 250nm and 500nm

SO2_LTO -21% As IEFs have been used up to the submission 2018, an EF comparison on aircraft level is not possible.

SO2_Cruise -37%

An analysis of international flight movements in the year 2015 has shown that the following air-crafts hold the strongest shares in flown distances having together a share of 92% (the first three types holding 52%): A320 with 26% A319 with 14% B777 with 12%

100 It should be noted that the Fokker 70 (F70) was labelled as a F100 due to the fact that the old CORINAIR spread-

sheet did not include the F70 aircraft.



F100 with 9% A321 with 8% B767 with 8% B737 with 7% DH8D with 5% B737_100 with 1%

It should be noted that in the old spreadsheet the A320 was the equivalent aircraft type also for the A319. Thus, no comparison is possible. The B777 was the equivalent aircraft type for B778, B77W, B77L, B773, B772. In the new emission factor spreadsheet for some of these aircrafts specific emission factors are now provided: B772, B773, B77W. The B777 does not exist any-more in the new spreadsheet, thus only the A320 and the A319 (which used to be an A320) will be compared in detail for explaining the following differences in international emissions.

Table 176: Deviations in EFs of aircraft type A320.

INTERNATIONAL Deviation Deviaton in emission factors

A320

NOx_LTO +1% +1%

NOx Cruise +14% +5% on weighted average for distance classes 250 nm and 500 nm

HC_LTO -73% As IEFs have been used up to the submission 2018, an EF comparison on aircraft level is not possible.

HC_Cruise -59%

CO_LTO -54% -52%

CO_Cruise +56% +179% on weighted average for distance classes 250nm and 500nm

SO2_LTO -22% As IEFs have been used up to the submission 2018, an EF comparison on aircraft level is not possible.

SO2_Cruise -16%

Up to submission 2017 for HC the IEFs from the national flight study (KALIVODA/KUDRNA 2002) were taken as shown below. The new HC EFs result in lower absolute HC and CH4 emissions. The HC IEF for domestic LTO is 88% lower; for international LTO 71% lower which is in line with the deviations shown in Figure 39. The HC IEF for domestic cruise is 64% lower; for inter-national cruise 59% lower which is in line with the deviations shown in Figure 39.

Table 177: Implied emission factors of HC for IFR kerosene for 2015.

kg/kg fuel DOMESTIC INTERNATIONAL

KALIVODA/KUDRNA 2002 IEFs

Tier 3A updated

IEFs KALIVODA/KUDRNA

2002 IEFs Tier 3A updated

IEFs

HC_LTO 0.008 0.001 0.005 0.0014

HC_Cruise 0.001 0.001 0.0008 0.0003

Up to submission 2017 for SO2 the IEFs from the national flight study (KALIVODA/KUDRNA 2002) were taken as shown below. The new SO2 EFs result in lower absolute SO2 emissions. All SO2 IEF are lower by 16% which is in line with the deviations shown in Figure 39.



Table 178: Implied emission factors of HC for IFR kerosene for 2015.

kg/kg fuel DOMESTIC INTERNATIONAL


Tier 3A updated IEFs


Tier 3A updated IEFs

SO2_LTO 0.001 0.00084 0.001 0.00084

SO2_Cruise 0.001 0.00084 0.001 0.00084

In a second step (validation 2), the results for the year 2015 of the submission 2017 with the old aircraft types and emission factors were compared with the results when the same activity data is being calculated with the new set of available aircraft types and emission factors and the new distance calculation formula.

Figure 41: Deviation of emissions of 1.A.3.a Civil Aviation ‒ Validation 2.

The new distance calculation is based on great circle distances between airport pairs and only leads to changes in FC cruise and emissions for cruise. For domestic flights the accuracy of dis-tances flown is increased by 5.5% on average leading to an increase of FC and emissions for cruise. For international flights the accuracy is improved by 0.5% on average resulting in slightly lower FC and emissions for cruise.

Harmonization of inventory and IEA data

In 2013 the ERT detected inconsistencies of fuel consumption data of domestic aviation and domestic navigation between the CRF tables and the IEA data (ICR 2013). In response to that it was explained that Austria uses a bottom-up approach to estimate fuel consumption whilst IEA relies on top-down approach based on fuel consumption statistics reported by Statistics Austria.

NOx_LTO NOx_Cruise HC_LTO HC_Cruise CO_LTO CO_Cruise SOx_LTO SOx_CruiseDomestic 0,0% 5,7% 0,0% 4,6% 0,0% 4,9% 0,0% 5,5%International 0,0% -0,4% 0,0% -0,5% 0,0% -0,4% 0,0% -0,5%

-2%

-1%

0%

1%

2%

3%

4%

5%

6%

[%]

Deviation of 1.A.3.a Civil Aviation IFR LTO and cruise emissions Validation 2 compared to Validation 1


NOx_LTO NOx_Cruise HC_LTO HC_Cruise CO_LTO CO_Cruise SOx_LTO SOx_Cruise



After having discussed this issue with Statistics Austria an Explanatory Note (30/09/2013) has been compiled by Statistics Austria declaring that a regular adoption of inventory data for the split between national and international fuel consumption in civil aviation and navigation in the national statistics will be adopted in the future, as far as the data can be submitted in time (early November).

As part of the regular QA/QC, the energy split between national and international aviation is provided to Statistics Austria for the IEA statistics based on the bottom-up model used to calcu-late the annual emission inventory.

Comparison IEA (military jet kerosene data)

In 2014, the ERT noted a significant difference in jet kerosene consumption (civil aviation) be-tween IEA data and CRF Table 1.C. In response to the draft ARR 2014, Austria explained that the IEA value also includes military jet kerosene data and that this is the reason for the differ-ence.

Completeness

In response to a question raised by the ERT (ICR 2013) it was explained that emissions of ground activities at domestic airports are also included, even if they are not separately reported under 1.A.3.a Aviation. This can be assured as Austria reports emissions from total fuel sold from the energy balance.

The approach in the Austrian inventory is as follows: After calculating fuel consumption for in-land road transport and off-road transport using a bottom-up approach (NEMO, GEORG), the sum of this fuel used is compared with the total fuel sold from the national energy balance (for details see 1.A.3.b Road Transport). The difference is then allocated to fuel export, which in-cludes fuel consumption for ground activities at airports and harbors as well, including fuel con-sumption by unregistered vehicles. As the fuel consumption reported under fuel export is in-cluded in the national totals101, an underestimation of emissions can be excluded.

Category-specific Recalculations

No recalculations were made

Category-specific Planned Improvements

No category-specific improvements are planned.

3.2.5 NFR Memo Item 1.A.3.a Civil Aviation – Cruise

In 2018, the share of Civil Aviation – Cruise in the total fuel consumption in the aviation sector in Austria amounted to 86% (without kerosene of military aviation). Emissions and activity data from aviation assigned include the transport modes domestic and international cruise traffic for IFR-flights.

101 GHG emissions from fuel export are included in 1.A.3.b, and are presented separately in Table 66 (Chapter

3.2.12.2)




Emissions from International Bunkers have been calculated using the methodology and emis-sion factors as described in Chapter 1.A.3.a Civil aviation.

Activity Data

Activity data of domestic and international cruise increased over the period from 1990–2018 by about 61% and 175% respectively which is shown in the following table.

Table 179: Activities for Civil Aviation – Cruise: 1990–2018.

Year Kerosene

Domestic cruise [TJ] International cruise [TJ]

1990 195 10,943

1991 257 12,251

1992 318 13,224

1993 380 13,909

1994 442 14,361

1995 503 16,134

1996 558 17,900

1997 612 18,568

1998 667 19,147

1999 705 18,588

2000 571 20,406

2001 527 19,944

2002 525 17,963

2003 527 16,621

2004 543 19,712

2005 571 23,212

2006 593 24,471

2007 615 25,915

2008 540 25,935

2009 506 22,314

2010 480 24,366

2011 429 25,479

2012 409 24,330

2013 405 23,106

2014 371 23,098

2015 365 24,934

2016 310 27,551

2017 293 26,606

2018 314 30,138

1990–2018 61% 175%



Emission Factors

In the following tables activities and IEF for Civil Aviation – Cruise are presented. The jump from 2015 to 2016 for all gases except for NH3 and PM2.5 is due to the changed activity data and emission factors which were being used for calculating IFR flights from the year 2016 onwards.

Table 180: Activities and Implied emission factors for NEC gases and CO for Civil Aviation ‒ Cruise: 1990–2018.


1990 11,138 23.1 219.0 16.2 0.16 25.0

1991 12,508 23.1 220.3 16.3 0.16 25.0

1992 13,543 23.1 221.4 16.5 0.16 25.0

1993 14,289 23.1 222.5 16.7 0.16 25.0

1994 14,802 23.1 223.5 16.9 0.16 25.0

1995 16,638 23.1 224.4 17.2 0.16 25.0

1996 18,458 23.1 224.1 18.3 0.16 25.0

1997 19,181 23.1 223.9 19.2 0.16 25.0

1998 19,814 23.1 223.8 20.0 0.16 25.0

1999 19,293 23.1 224.2 20.0 0.16 25.0

2000 20,977 23.1 307.2 19.8 0.16 25.0

2001 20,471 23.1 308.9 19.8 0.16 25.0

2002 18,488 23.1 306.8 19.8 0.16 25.0

2003 17,147 23.1 303.8 19.9 0.16 25.0

2004 20,255 23.1 300.8 19.8 0.16 25.0

2005 23,784 23.1 293.8 19.8 0.16 25.0

2006 25,064 23.1 300.8 19.8 0.16 25.0

2007 26,529 23.1 301.3 19.8 0.16 25.0

2008 26,475 23.1 298.3 19.8 0.16 25.0

2009 22,820 23.1 300.8 19.8 0.16 25.0

2010 24,846 23.1 305.7 19.8 0.16 25.0

2011 25,907 23.1 307.9 19.7 0.16 25.0

2012 24,739 23.1 310.4 19.7 0.16 25.0

2013 23,512 23.1 317.4 19.7 0.16 25.0

2014 23,469 23.1 319.1 19.7 0.16 25.0

2015 25,300 23.1 323.3 19.7 0.16 25.0

2016 27,860 19.4 369.1 8.2 0.16 25.0

2017 26,898 19.4 374.0 7.5 0.16 25.0

2018 30,451 19.4 378.9 7.3 0.16 25.0

Emission factors for heavy metals are presented in chapter 3.2.8.


No recalculations have been made in this year’s submission




No category-specific improvements are planned.

3.2.5.1 NFR Memo Item 1.A.3.d International maritime Navigation

Austria does not have any activities under Memo 1 a 3 d International maritime navigation. Ac-tivities under International inland waterways are included in the national total according to the reporting under CLRTAP.

3.2.6 NFR 1.A.3.b Road Transport

Emissions from road transportation are covered in this category. It includes emissions from pas-senger cars, light duty vehicles, heavy duty vehicles and busses, mopeds and motorcycles, gasoline evaporation from vehicles as well as vehicle tyre, brake and road surface wear.

Road Transport is the main emission source for NOx, SO2, NMVOC and NH3 emissions of the transport sector. Up to 2005 especially classic air pollutants from road transport – NOx and PM emissions – have increased with constantly rising vehicle kilometres mainly because of: steady increase of transport activity altered spatial structures: urban sprawl and centralization changing demand structures in the industry: growing division of labour and flexible production

methods (just-in-time production) cause the inventory being replaced by means of transport disproportionately existing infrastructure for motorized individual transport and further devel-

opment changed lifestyle and mobility needs of the population fuel exports by – especially in comparison with Germany and Italy – cheap fuel prices in Austria

Technical improvements and a stricter legislation, however, led to a reduction of emissions per vehicle or per mileage respectively of mostly all other air pollutants.


Mobile road combustion is differentiated into the categories Passenger Cars, Light Duty Vehi-cles, Heavy Duty Vehicles and Buses, Mopeds and Motorcycles. In order to apply the EMEP/EEA methodology a split of the fuel consumption of different vehicle categories is needed.

Bottom up Methodology – Fuel consumed

Energy consumption and emissions of the different vehicle categories are calculated by multi-plying the yearly road performance per vehicle category (km/vehicle and year) by the specific energy use (g/km) and by the emission factors in g/km (Model: NEMO).

NEMO also models the road performance and emissions per vehicle size, age and motor type based on dynamic vehicle specific drop out- and road performance functions.

To determine fuel consumption and emissions of domestic road transport, vehicle stock and to-tal annual road performance (mileage driven per year) of the vehicle categories should be rec-orded as precisely as possible.



The traffic volumes up to and including 2007 are taken from Austrian National Transport Model “VMOe 2025+” Verkehrs-Mengenmodell-Österreich (Federal Transport Model, Ministry of Transport, BMVIT, not published).

Mileage data after 2007 to submission 2019 is calculated from the growth rates according to the final results of the automatic traffic counting stations and the toll data.

In this year’s submission the traffic volume sources are as follows:

For the first time, data from the periodic roadworthiness tests has been evaluated resulting in new age-related mileage data. This affects the categories PC, LDV and MC. In the case of cars, the analysis of this new data source led to the following findings (SCHWINGSHACKL, M.; REXEIS, M.. (2019a): old vehicles drive more than previously assumed and in general the specific mileage per car per vehicle age- year is lower than previously assumed These facts generally lead to a decrease in the total domestic mileage of passenger cars

over the entire time series

The data quality for these vehicle categories could thus be significantly improved.

The data source of the previous submissions has been retained for heavy commercial vehicles and buses (VMOe 2025+” Verkehrs-Mengenmodell-Österreich + growth rates according to the final results of the automatic traffic counting stations and the toll data).

Top down Methodology – Fuel sold

Based on the NEMO model fuel consumption and emissions for road transport are calculated with a bottom-up approach. Calculated fuel consumption of road transport is then summed up with calculated fuel consumption of off road traffic and is compared with national total fuel sold.

The difference between the fuel consumption calculated in the bottom-up methodology for road traffic plus off-road transport within Austria and total fuel sales in Austria (obtained from the yearly Austrian energy balance) is allocated to fuel export (fuel sold in Austria but consumed abroad).

The emissions reported for Austria also include the emissions from the fuel exports.

Fuel export102

Since the end of the nineties an increasing discrepancy between the total Austrian fuel sales and the computed domestic fuel consumption became apparent. From 2003 onward this gap accounts for roughly 30% of the total fuel sales. A possible explanation of this discrepancy is the „fuel export in the vehicle tank” – due to the relatively low fuel prices in Austria (in compari-son to the neighbouring countries). Meaning that to a greater extent fuel is filled up in Austria and consumed abroad. This assumption is underpinned by two national studies (MOLITOR et al. 2004; MOLITOR et al. 2009).

It is assumed that the fuel export fleet (mainly travelling on highways) is similar to the Austrian fleet on highways, which means that no different efficiency rates are assumed for the fuel export fleet. It is assumed that fuel export is assigned to three vehicles groups: gasoline PC, diesel PC and diesel trucks.

102 Under the LRTAP Convention national emissions are reported based on fuel sold (including fuel export); under the

NEC Directive national emissions are reported based on fuel used (excluding fuel export).



Gasoline fuel export is calculated from the inland gasoline consumption and the difference to the total sales of gasoline in Austria. The difference is being assigned to the gasoline fuel export in cars. Fuel consumption of diesel fuel export with cars is being calibrated in proportion to the diesel share of the foreign car fleet based on the relation between FC of gasoline cars in fuel export and FC of gasoline cars in inland. After having calculated the diesel export in cars the diesel export of trucks can be estimated by total diesel sales minus diesel FC inland minus die-sel export in cars (HAUSBERGER/SCHWINGSHACKL/REXEIS 2015, p.22).

NEMO – Network Emission Model

Emissions from Mobile Combustion have so far been calculated with the model GLOBEMI (HAUSBERGER 1997; HAUSBERGER/SCHWINGSHACKL/REXEIS 2015a,b). The calculations have been based on a detailed depiction of fleet composition, driving behaviour, related energy consump-tion and emission factors.

From the submission in 2015 (1990–2013) onwards calculations are based on the model NEMO – Network Emission Model (DIPPOLD/REXEIS/HAUSBERGER 2012; HAUSBERGER/ SCHWINGSHACKL/ REXEIS 2015a,b, 2018). NEMO is set up on the same methodology as the former model GLOBEMI and combines a detailed calculation of the fleet composition with the simulation of energy consumption and emission output on vehicle level. It is fully capable to depict the up-coming variety of possible combinations of propulsion systems (internal combustion engine, hy-brid, plug-in-hybrid, electric propulsion, fuel cell …) and alternative fuels (CNG, biogas, FAME, Ethanol, GTL, BTL, H2 …).

In addition, NEMO has been designed to be also suitable for all main application fields of simu-lation of energy consumption and emission output on a road-section based model approach. As there does not yet exist a complete road network for Austria on a highly resolved spatial level, the old methodology based on a categorisation of the traffic activity into “urban”, “rural” and “mo-torway” has been currently also applied in NEMO.

The model calculates vehicle mileages, passenger-km, ton-km, fuel consumption, all exhaust gas emissions, evaporative emissions and suspended TSP, PM10, PM2.5, PM1 and PM0.1 exhaust and non-exhaust emissions of road traffic. The balances use the vehicle stock and functions of the km driven per vehicle and year to assess the total traffic volume of each vehicle category.

Model input is: 1) Vehicle stock of each category split into layers according to the propulsion system (SI, CI,..),

cylinder capacity classes or vehicle mass; 2) Emission factors of the vehicles according to the year of first registration and the layers from 1); 3) Yearly growth rates of kilometres driven by PCs and HDVs separated for the federal street

network (motorways) and the federal county network (urban, rural) (BMVIT 2019) 4) Number of passengers per vehicle and tons payload per vehicle; 5) Optional either/or total gasoline and diesel consumption of the area under consideration, average km per vehicle and year.

Following data is calculated: a) Km driven per vehicle and year or total fuel consumption, b) Total vehicle mileages, c) Total passenger-km and ton-km, d) Specific emission values for the vehicle fleets [g/km], [g/t-km], [g/pass-km], e) Total emissions (CO, HC, NOx, particulate matter, CO2, SO2 and several unregulated pollu-

tants among them CH4 and N2O) and energy consumption (FC) of road traffic.



Figure 42 shows a schematic picture of the methodology of NEMO.

Figure 42: Schematic picture of the NEMO model.

The calculation is done according to the following method for each year: 1) Assessment of the vehicle stock split into layers according to the propulsion system (SI,

CI,..), cylinder capacity classes (or vehicle mass for HDV) and year of first registration using the vehicle survival probabilities and the vehicle stock of the year before.

iii Jg1iyear ,Jgiyear ,Jg yprobabilit survivalss ×= −tocktock 2) Assessment of the km per vehicle for each vehicle layer using age and size dependent func-

tions of the average mileage driven. If option switched on, iterative adaptation of the km per vehicle to meet the total fuel consumption targets.

3) Calculation of the total mileage of each emission category (e.g. passenger car diesel, EURO 3)

)km/vehicle (stock=mileage total iyear ,Jg

end

start.=Jgiyear Jg,E ii ∑ ×

4) Calculation of the total fuel consumption and emissions of each emission category

iE,KEE jiifactoremission mileage total=Emission ×

5) Calculation of the total fuel consumption and emissions of each vehicle category

i

i

E1E

ryveh.catego Emission=Emission ∑=

end

6) Calculation of the total passenger-km and ton-km

)loadingmileage vehicle(=volumestransport ii

i

EE1E

ryveh.catego ×∑=

end

7) Summation over all vehicle categories

with Jgi ... Index for a vehicle layer (defined size class, propulsion type, year of first registration) Ei Index for vehicles within a emission category (defined size class, propulsion type and exhaust certification level)



Activity Data

From 2017 to 2018 fuel consumption in TJ (gasoline, diesel and alternative fuels including liquid biomass) of road transport increased by 0.7%. Specific consumption per average vehicle kilo-meter per vehicle category did not improve for diesel passenger cars and light duty vehicles be-tween 2017 and 2018; it declined by 0.9% for gasoline passenger cars, and by 0.7% for heavy duty vehicles. .

The following table gives an overview of the amount of fuel sold in Austria (including fuel export) differentiated by fuel type.

Table 181: Activities from 1.A.3.b Road Transport differentiated by fuel type: 1990–2018.

Fuel consumption (based on fuel sold) [TJ]

Year total gasoline diesel oil LPG gaseous biomass 1990 176,826 103,899 72,514 413 - - 1991 196,386 113,961 81,998 428 - - 1992 196,215 108,959 86,811 444 - - 1993 198,243 104,519 93,273 451 - - 1994 199,009 100,775 97,772 462 - - 1995 202,791 97,340 104,957 494 - - 1996 224,095 90,040 133,386 670 - - 1997 210,964 85,342 125,092 530 - - 1998 237,523 89,286 147,648 590 - - 1999 229,403 82,982 145,799 622 - - 2000 241,747 80,175 160,901 672 - - 2001 259,856 80,754 178,379 722 - - 2002 288,170 86,946 200,239 984 - - 2003 311,792 88,915 221,744 1,132 - - 2004 318,769 86,497 231,311 947 14 - 2005 325,692 84,058 238,568 977 16 2,073 2006 313,467 80,670 223,912 1,005 15 7,865 2007 317,097 78,772 228,455 968 76 8,827 2008 299,955 70,770 217,129 1,002 137 10,916 2009 295,039 70,553 209,058 945 330 14,153 2010 306,694 69,420 220,849 889 453 15,083 2011 296,496 66,867 213,508 854 485 14,782 2012 296,250 65,089 214,317 900 533 15,412 2013 309,917 63,803 229,446 901 648 15,118 2014 302,483 62,558 222,523 788 700 15,914 2015 309,533 63,137 227,440 613 723 17,620 2016 319,311 62,428 239,071 473 717 16,622 2017 327,189 61,695 248,726 478 710 15,581 2018 329,567 63,172 249,600 373 689 15,733 1990–2018 86% -39% 244% -10% 4695%103 659%104

103 Trend 2004-onwards



In the following table NOx emissions are disaggregated by means of road transportation. Inland emissions and those from fuel export are shown separately in the two relevant vehicle catego-ries passenger cars and heavy duty vehicles and must be summed up to get the total emissions for each vehicle category. The phenomenon of fuel export is explained in the subchapter Meth-odological Issues.

Table 182: NOx emissions from 1.A.3.b Road Transport differentiated by means of transportation 1990–2018.

Year Passenger cars light duty vehicles

heavy duty vehicles

mopeds & motorcycles

inland fuel export inland inland fuel export inland NOx [kt]

1990 56,45 3,76 7,30 35,42 13,55 0,13

1991 53,95 9,24 7,34 38,65 15,96 0,13

1992 52,45 5,31 7,59 38,98 16,42 0,13

1993 49,60 3,50 7,67 38,23 18,20 0,14

1994 48,31 1,57 7,93 38,26 16,11 0,14

1995 46,29 0,96 8,02 38,32 16,83 0,15

1996 45,37 -1,69 8,25 38,48 36,89 0,16

1997 44,16 -2,46 8,36 38,99 23,58 0,18

1998 43,76 0,16 8,47 39,53 34,42 0,19

1999 43,63 -2,05 8,48 39,99 28,27 0,21

2000 43,68 -1,97 8,38 41,01 34,21 0,21

2001 44,24 0,18 8,42 40,62 39,74 0,22

2002 45,73 5,53 8,76 40,24 42,54 0,23

2003 47,37 9,44 9,28 40,59 45,33 0,24

2004 48,32 11,03 9,79 40,17 43,54 0,25

2005 48,30 12,46 10,08 39,94 44,27 0,26

2006 48,47 12,05 10,45 39,93 33,08 0,26

2007 48,99 13,38 10,80 37,71 27,90 0,26

2008 47,15 11,98 10,65 33,53 22,53 0,26

2009 46,02 12,87 10,65 28,50 20,19 0,26

2010 46,77 12,83 10,95 26,66 21,13 0,25

2011 47,43 11,81 11,12 25,35 15,36 0,25

2012 47,25 11,44 11,05 23,13 14,71 0,25

2013 47,92 10,73 11,07 21,39 17,72 0,25

2014 49,20 10,39 11,16 19,64 13,24 0,25

2015 49,93 11,63 11,23 17,05 10,81 0,24

2016 49,13 11,87 11,03 14,75 8,42 0,24

2017 46,39 11,69 10,34 12,61 6,84 0,23

2018 44,26 9,87 9,99 11,05 5,25 0,23

1990–2018 -22% 163% 37% -69% -61% 84%

104 Trend 2005-onwards



In 2018, the total share of fuel export in 1.A.3.b amounted to 19% or 15.1 kt NOx of which 65% are attributed to passenger road transport and 35% to road freight transport.

Figure 43: Share of fuel export (NOx) in 1.A.3.b Road Transport in 2018.

The general equal distribution of pure biofuels to relevant vehicle categories was changed in the calculations of the 2016 submission. The allocation has been done based on expert judgement and was implemented in the model NEMO according to the road performance of each vehicle category: biodiesel B100 is assigned to HDV to 100% vegetable oil is assigned to HDV to 100%105 bioethanol (E85) is assigned to PC to 100% The allocation of alternative fuels like liquefied petroleum gas (LPG) and compressed natural gas (CNG) is assumed in the model as follows: LPG is assigned to PC, HDV and LDV (only otto-motorised) according to their road perfor-

mance. Natural gas (CNG) is distributed to passenger cars, HDV and LDV (only otto-motorised) ac-

cording to their road performance. Biofuels

Since 2005 biogenic fuel (biodiesel, bioethanol, plant oil) has been used in the Austrian road transport sector. Biodiesel and bioethanol are mainly used for blending fossil fuels, whereas plant oil is distributed in pure form. In 201 the energetic substitution by biofuels amounted to 6.25% in the road transport sector (BMNT 2019a).106 2005, the first year of blending biofuels, the substitution amounted to only 0.8% (UMWELTBUNDESAMT 2006c).

105 An allocation to agriculture is not possible at the moment, because of the technical model framework. 106 The required substitution target amounts to 5.75%, measured by energy content.

19%

55%

12%

14% 0%

Share of fuel export in 1.A.3.b in 2018

fuel export

passenger cars

light duty vehicles

heavy duty vehicles

mopeds and motorcycles




For the year 2018 a consumption of 462 396 tons of HVO107 & biodiesel (for blending with die-sel) and 88.206 tons of bioethanol (for blending with gasoline) are used as input data in the calculation models based on NEMO and GEORG (see 1.A.2.g.vii). The following amounts are used in pure form: 63 177 tons of biodiesel and plant oil; 310 (in 1 000m3) of biogas (BMNT 2018a).

Table 183: Use of biofuels in absolute figures 2005–2018.

Year pure blended biofuels total [t] biofuel pure [t] biogas [1000m3] biodiesel [t] bioethanol [t]

2005 17.000 0 75.000 0 92.000

2006 52.500 0 288.000 0 340.500

2007 89.209 0 298.828 20.391 408.428

2008 121.276 0 304.291 84.910 510.477

2009 133.690 2 405.909 99.424 639.025

2010 92.377 1 427.000 105.883 625.261

2011 101.824 3 422.072 102.755 626.652

2012 74.983 13 440.938 105.378 621.312

2013 80.536 25 443.389 88.842 612.792

2014 159.153 640 474.692 87.688 722.173

2015 174.255 490 528.944 89.557 793.246

2016 80.875 469 495.764 86.912 664.020

2017 46.613 186 459.032 85.226 591.057

2018 63.177 310 462.396 88.206 614.089

2005–2018 272% 19495%108 517% 333%109 567%

Emission Factors

Emission factors used for NEMO (Version 5.0.1) are based on a representative number of vehi-cles and engines measured in real-world driving situations taken from the „Handbook of Emis-sion Factors” – HBEFA (HAUSBERGER & KELLER et al. 1998) and on ARTEMIS measurements (basically for passenger cars, light duty vehicles and motorcycles) which are taken into account in HBEFA. The latest HBEFA Version V4.1 published end of August 2019 has been applied (MATZER C., WELLER K.,et. al 2019).

Summarized innovations in HBEFA Version 4.1: All emission factors for the “warm operating condition” have been updated based on: New emission measurements are available. PEMS and “Dieselgate” have made large

amounts of new measurement data available since the last HBEFA version For the first time, the influence of the ambient temperature on the NOx exhaust-aftertreatment

systems was implemented. The lower the ambient temperature, the worse these systems work. This resulted in an increase in the emission-factors for diesel cars and light duty vehi-cles (Euro 3- Euro 6)

107 HVO…Hydrotreated Vegetable Oils 108 Trend 2009-onwards 109 Trend 2007-onwards



New traffic situations and driving cycles with revised dynamic parameters HBEFA4.1 shows the effect of the mandatory software update of VW vehicles with the EA189

engine ("Diesel Gate") on the average Euro 5 emission factor Influence of age on exhaust gas aftertreatment systems: So far, constant emissions have been assumed for mileage greater than 50,000 km. In

HBEFA 4.1. This was changed based on remote sensing data. This leads to an increase in pollutant emissions up to mileage of 250,000km. This also has retroactive effects for the past few years and an effect on NOx emissions

Moreover, specific CO2 emission factors of new passenger cars and light duty vehicles accord-ing to the national CO2 monitoring data for the Austrian fleet, have been implemented (BMNT 2019b, c). Cold-start emissions

Cold-start emissions are calculated as an extra emission over the emissions that would be ex-pected if all vehicles were only operated with hot engines and warmed-up catalysts. Cold-start emissions are only allocated for urban and rural driving, as the number of starts in highway conditions seems to be relatively limited. Cold-start emissions are calculated in NEMO for each vehicle category and each pollutant as follows:

Additional impact per start [g / km] = cold-start surcharge [g / start] / average trip length per cold start [km / start]

The cold start influence is in NEMO included in the calculation of fuel consumption and emis-sions of CO2, NOx, CO, hydrocarbons and PM. For N2O and NH3 no cold start emission factors were found in the literature.

The values used for cold-start surcharges come from: PC and LDV: cold-start model (updated in HBEFA 3.2 and integrated in HBEFA V.3.3) HDV: cold-start study commissioned by Umweltbundesamt (REXEIS et al. 2013) 2-wheelers: derived from cold-start emissions of PC gasoline Exhaust emissions – PM

Emission factors used for (PM2.5 and PM10) include the condensable component. As condensa-ble means "condensing on the filter at <52° C", this definition is exactly in line with the PM measurement rules on the emission test benches for road vehicles and NRMM. Also see Table “Information on PM emission factors” in the Annex (chapter 12.3).

Exhaust emissions of mopeds and motorcycles ‒ PM

Up to submission 2018 PM emissions of mopeds and motorcycles were reported as IE which should have been NE. These emissions were not reported, as no country-specific measure-ments for mopeds and motorcycles are available.

For the submission 2019, NEMO 4.0.3 has used the Tier 2 method from the EMEP/EEA 2016 Guidebook for particulate matter emissions (exhaust) in two-wheeled vehicles. This improve-ment has been made following a recommendation of the stage 3 CLRTAP Review 2017.

In this year’s submission, the newest NEMO 5.0.1 version uses emission factors from the new-est HBEFA Version (Version 4.1). The emission factors are based on vehicle measurements,



Non-exhaust emissions ‒ PM From the submission 2018 onwards non-exhaust emissions from brake/tyre wear and road abrasion (road surface wear) are reported separately under 1.A.3.b.6 and 1.A.3.b.7. This results in a revised time-series for 1.A.3.b.7 and a completely new time-series for 1.A.3.b.6. This im-provement was made following a recommendation of the stage 3 CLRTAP Review 2017 and the NEC Review 2017.

Regarding non-exhaust emissions, the EMEP/EEA 2016 Guidebook puts a focus on primary particles. Following, road resuspension of previously deposited material, is not being reported any longer from the submission 2017 onwards, but can be provided when needed.

No information is given in the EMEP/EEA Guidebook 2016, if the condensable fraction is rele-vant in non-exhaust emission factors (PM2.5 and PM10). Also see Table “Information on PM emission factors” in the Annex (chapter 12.3).

Gasoline evaporation ‒ NMVOC In the submission 2018 Austria has adopted the method for 1.A.3.b.v according to the EMEP/EEA 2016 Guidebook. Total evaporative emissions are now including diurnal losses, hot soak and running losses. The emissions of these three subcategories for 1.A.3.b Road Transport are displayed below and can be reported separately. This improvement was made following a recommendation of the NEC Review 2017.

Table 184: NMVOC emissions from evaporation in 1.A.3.b. Road Transport

Year diurnial losses Hot soak running losses [kt]

1990 0.7 5.0 14.0

1991 0.6 4.5 12.7

1992 0.6 4.1 11.6

1993 0.6 3.6 10.1

1994 0.5 3.2 8.9

1995 0.5 2.7 7.6

1996 0.4 2.3 6.4

1997 0.4 1.9 5.3

1998 0.3 1.6 4.4

1999 0.3 1.3 3.6

2000 0.3 1.1 2.9

2001 0.3 0.9 2.3

2002 0.2 0.7 1.9

2003 0.2 0.6 1.6

2004 0.2 0.5 1.3

2005 0.2 0.4 1.1

2006 0.1 0.3 0.6

2007 0.1 0.2 0.6

2008 0.1 0.2 0.5

2009 0.1 0.2 0.4



Year diurnial losses Hot soak running losses [kt]

2010 0.1 0.1 0.4

2011 0.1 0.1 0.3

2012 0.1 0.1 0.3

2013 0.1 0.1 0.3

2014 0.1 0.1 0.3

2015 0.1 0.1 0.3

2016 0.1 0.1 0.2

2017 0.1 0.1 0.2

2018 0.1 0.1 0.2

Relative factors used on top of commercial fuels incl. blending of biofuels (=reference fuels)

As a consequence of the provisional main findings in the CRR 2016 it shall be explained that all emission factors of alternative and pure biofuels used in NEMO are considered in the model by relative factors compared to commercial fuels. The following table provides the used relative factors compared to the reference fuels. The reference fuels are blended gasoline and blended diesel, because these fuels are commercially launched by fuelling stations on the market. The relative factors are multiplied with the EFs (in g/km) of every EURO-class and vehicle category per year. The relative factors are kept constant for the whole time series, but of course the final EFs change over time, because the basic EFs per EURO class improve as a consequence of the vehicles' advanced exhaust gas technologies. The relative factors are derived from literature research (EMEP Guidebook if available) or exhaust measurements.

Table 185: Relative factors used for bioethanol E85 and biogas.

Gasoline blended gasoline bioethanol E85 biogas

FC 1.00 1.00 0.84

NOx 1.00 1.51 0.67

HC 1.00 1.37 0.44

CO 1.00 0.88 0.70

PM exhaust 1.00 1.00 0.71

Nox_raw 1.00 1.51 0.67

N2O 1.00 0.64 0.34

NO2 1.00 1.51 1.11

NH3 1.00 1.00 0.68

CH4 1.00 1.94 2.94

Benzol 1.00 1.00 1.00

C22H12 1.00 1.00 1.00

C20H12 (k) 1.00 1.00 1.00

C20H12 (b) 1.00 1.00 1.00

C20H12 (a) 1.00 1.00 1.00



Table 186: Relative factors used for biodiesel, plant oil and diesel B20.

Diesel blended diesel biodiesel (RME) plant oil diesel B20

FC 1.00 1.00 1.00 1.00

NOx 1.00 1.20 1.20 1.04

HC 1.00 1.00 1.00 1.00

CO 1.00 0.74 0.74 0.95

PM exhaust 1.00 0.61 0.61 0.92

Nox_raw 1.00 1.20 1.20 1.04

N2O 1.00 1.20 1.20 1.04

NO2 1.00 1.00 1.00 1.00

NH3 1.00 1.00 1.00 1.00

CH4 1.00 1.15 1.15 1.03

Benzol 1.00 1.00 1.00 1.00

C22H12 1.00 1.00 1.00 1.00

C20H12 (k) 1.00 1.00 1.00 1.00 C20H12 (b) 1.00 1.00 1.00 1.00

C20H12 (a) 1.00 1.00 1.00 1.00

The following tables present the IEFs for 1.A.3.b Road Transport. The IEFs change over time due to new technologies.



Table 187: Activities and Implied emission factors for NEC gases for 1.A.3.b Road Transport: 1990–2018.

Year Activity IEF SO2 IEF NOx IEF NMVOC IEF NH3 IEF PM2.5 [TJ] [t/PJ] 1990 176,826 27.0 659.4 546.4 4.5 3.78 1991 196,386 27.4 637.8 486.0 6.0 3.54 1992 196,215 28.8 616.1 433.3 7.2 3.70 1993 198,243 30.4 591.9 376.9 8.3 3.74 1994 199,009 31.4 564.4 333.3 9.1 3.88 1995 202,791 28.0 545.3 288.0 9.8 3.91 1996 224,095 12.4 568.8 225.8 9.2 3.66 1997 210,964 11.5 534.6 203.5 10.2 3.98 1998 237,523 10.9 532.7 167.5 10.4 3.66 1999 229,403 10.2 516.7 145.7 10.8 3.90 2000 241,747 9.6 519.2 121.9 10.4 3.80 2001 259,856 9.2 513.5 104.2 10.0 3.61 2002 288,170 7.9 496.3 90.4 9.7 3.35 2003 311,792 7.2 488.3 78.8 9.1 3.18 2004 318,769 0.6 480.3 70.4 8.5 3.16 2005 325,692 0.5 476.9 62.8 7.9 3.11 2006 313,467 0.4 460.2 52.2 7.9 3.31 2007 317,097 0.4 438.4 46.4 7.3 3.33 2008 299,955 0.4 420.4 42.0 6.9 3.44 2009 295,039 0.4 401.6 38.0 6.5 3.41 2010 306,694 0.4 386.7 33.1 6.0 3.34 2011 296,496 0.4 375.4 30.3 5.5 3.53 2012 296,250 0.4 364.0 27.3 5.0 3.53 2013 309,917 0.4 352.0 24.0 4.3 3.41 2014 302,483 0.4 343.4 22.2 4.0 3.59 2015 309,533 0.4 326.0 20.4 3.8 3.59 2016 319,311 0.4 298.9 18.4 3.6 3.60 2017 327,189 0.4 269.3 16.5 3.4 3.59 2018 329,567 0.4 244.7 15.5 3.4 3.72

Emission factors for heavy metals and POPs are presented in chapter 3.2.8.


Quality management for input data of 1.A.3.b Road Transport is implemented by carrying out the following checklist after receipt of input data: Are the correct values used (check for transcription errors)? Check of plausibility of input data (time-series order of magnitude)! Is the data set complete for the whole time series? Check of calculation units! Check of plausibility of results (time-series order of magnitude)! Are all references clearly made? Are all assumptions documented?




There have been recalculations in all subcategories of 1.A.3.b.Road Transport due to the new version of the emissions factor database (HBEFA Version 4.1).

Overall shifts of Fuel Cosumption and emissions between inland and fuel export

The domestic activity data (fuel consumption/mileage) has fundamentally been updated with new specific mileage per vehicle category: For the first time, data from the periodic roadworthi-ness tests has been evaluated resulting in new age-related mileage data and improved data-accuracy. This affects the categories passenger cars (PC), light duty vehicles (LDV) and motor-cycles (MC). Update/Improvement of methodology and emission factors

By using the latest version of the emission model "NEMO" from the Graz University of Technol-ogy to calculate traffic emissions, the following improvements to the model and the input data resulted in emission changes as described below:

New specific mileage per vehicle category: For the first time, data from the periodic roadwor-thiness tests has been evaluated resulting in new age-related mileage data. This affects the categories PC, LDV and MC. In the case of cars, the analysis of this new data source led to the following findings: old vehicles drive more than previously assumed and in general the specific mileage per car per vehicle age-year is lower than previously assumed These facts generally lead to a decrease in the total domestic mileage of passenger cars

over the entire time series. New and improved emissions factors for all vehicle categories The most recent version of the emission calculation model NEMO (TU-Graz) includes the re-

cently released emission factor database HBEFA 4.1. Within this new software version, all consumption factors were checked or revised.

The implementation of the new HBEFA Version 4.1 resulted in an increase in emission fac-tors for all vehicle categories. Due to the diesel gate and the mandatory PEMS measure-ments for the Euro 6d_temp standard, large amounts of new measurement data were availa-ble. New findings, such as the influence of ambient temperature on the functional efficiency of NOx exhaust after treatment systems (such as SCR), new aging functions of such systems, new improved traffic situations combined with revised dynamic parameters, led to an in-crease in specific emissions per vehicle category

For 2018, the above mentioned overlapping recalculations lead to the following overall changes to emissions from 1.A.3 Transport (excluding fuel exports): – 4,36 kt NOx, – 0.21 kt NMVOC, + 0.02 kt NH3, – 0.13 kt PM2.5. (Changes to emissions from 1.A.3 Transport including fuel ex-ports: – 7,77 kt NOx, – 0.34 kt NMVOC, – 0,002 kt NH3, – 0.21 kt PM2.5.)

NB: In the model NEMO every revision of inland FC leads to a direct shift between fuel con-sumption in inland and fuel export. In the emission model a lower fuel consumption in inland leads to higher activities in fuel export. Due to the Austrian methodology for estimating GHG from road transport (please see Methodology 1.A.3.b - fuel export), where the total fuel sold in Austria is subtracted by the inland road transport and the off-road transport to derive fuel ex-ports, there is no underestimation in total fuel consumption of 1.A.3 Transport plus mobile ma-chinery of NRMM, because the amount of total fuel sold in Austria taken from the energy bal-



ance is the value which determines the GHG emissions of transport. The recalculation therefore did not change the total GHG emissions from transport but only the contributions from the sub-categories. Category-specific Planned Improvements No category-specific improvements are planned.

3.2.7 Other mobile sources – Off Road

Off-road sources are mobile engines and mobile machinery in the NFR sectors 1.A.2.g.vii Indus-try, 1.A.3.c Railways, 1.A.3.d Navigation, 1.A.4.b.2 Household and Gardening, 1.A.4.c.2 Agricul-ture and Forestry and 1.A.5.b Military activities.

3.2.7.1 NFR 1.A.2.g.vii Off-road vehicles and other machinery


Energy consumption and emissions of off-road traffic in Austria are calculated with the model GEORG (Grazer Emissionsmodell für Off-Road Geräte). This model has been developed within a study about off-road emissions in Austria (HAUSBERGER 2000). The study was prepared to im-prove the poor data quality in this sector. The following categories were taken into account: 1.A.2.f Industry, 1.A.3.c Railways, 1.A.3.d Navigation, 1.A.4.b Household and Gardening, 1.A.4.c Agriculture and Forestry, 1.A.5 Military activities. Input data to the model are: Machinery stock data (obtained from data on licences, through inquiries and statistical ex-

trapolation); Assumptions on drop-out rates of machinery (broken down machinery will be replaced); Operating time (obtained through inquiries), related to age of machinery. From machinery stock data and drop-out rates an age structure of the off-road machinery was obtained by GEORG. Four categories of engine types were considered. Depending on the fuel consumption of the engine the ratio power of the engine was calculated. Emissions were calcu-lated by multiplying an engine specific emission factor (expressed in g/kWh) by the average en-gine power, the operating time and the number of vehicles.

With this method national fuel consumption and national emissions are calculated (bottom-up). Calculated fuel consumption of off-road traffic is then summed up with total fuel consumption of inland road transport and is compared with total fuel sold in Austria according to the national energy balance. The difference is allocated to fuel export (for details concerning fuel export see 1.A.3.b). The emissions reported for Austria also include the emissions from fuel exports as-suming that the fuel export fleet (mainly travelling on highways) is similar to the Austrian fleet on highways. The used methodology conforms to the requirements of the EMEP/EEA Tier 3 meth-odology.



Activity Data

Activity data, vehicle stock and specific fuel consumption for vehicles and machinery (e.g. lead-ers, diggers etc.), were taken from: Statistik Austria (fuel statistics), Questionnaire to vehicle and machinery users (HAUSBERGER 2000), Interviews with experts and expert judgment

validating the questionnaire results (HAUSBERGER 2000) and Information from vehicle and machinery manufacturers (HAUSBERGER 2000).

An allocation of pure biofuels on the off -road sector has not been performed due to lack of data.

Activities used for estimating the emissions of mobile sources in 1.A.2.g.vii are presented in Ta-ble 187. Activities include liquid fuels (diesel, gasoline and biofuels).

Emission Factors

The specific emission factors for mobile machinery and equipment used in 1.A.2.g.vii Industry and 1.A.4.c.2 Agriculture and Forestry were updated in the submission 2018 on the basis of available measurements (SCHWINGSHACKL/REXEIS/HAUSBERGER 2017). Emission factors for NOx, PM, CO and HC of diesel engines were updated for stages I up to IV of industrial and agri-cultural equipment. The NOx levels for example of stages I and II were slightly lowered by the update. For the emission levels IIIA, IIIB and IV, the update resulted in an increase of the NOx emission factors to a level well above the limit values.

The following tables show the updated exhaust emission factors for four categories of engine types (average motor capacity) depending on the year of construction used in the GEORG model for 1.A.2.g.vii Industry and 1.A.4.c.2 Agriculture and Forestry. They represent emissions according to the engine power output and also fuel consumption. They are close to the emission standards for diesel NRMM (Non-Road Mobile Machinery)..

Table 188: Emission factors for diesel engines < 56 kW.

Year NOx NH3 NMVOC PM [g/kwh]

AG1 11,992 0,0060 1,894 2,184

AG2 10,923 0,0045 1,446 1,682

Stage 1 6,555 0,0039 0,211 0,410

Stage 2 6,042 0,0029 0,146 0,214

Stage 3a 8,936 0,0020 0,077 0,079

Stage 3b 5,849 0,0020 0,033 0,034

Stage 4 5,849 0,0020 0,033 0,034

Stage 4 SCR 5,849 0,0020 0,033 0,034

Stage 5 3,286 0,0020 0,001 0,010



Table 189: Emission factors for diesel engines 56 - 80 kW.


AG1 11,992 0,0060 1,894 2,184

AG2 10,923 0,0045 1,446 1,682

Stage 1 6,555 0,0039 0,211 0,410

Stage 2 5,639 0,0029 0,146 0,214

Stage 3a 6,885 0,0020 0,077 0,079

Stage 3b 4,347 0,0020 0,033 0,034

Stage 4 2,254 0,0020 0,027 0,027

Stage 4 SCR 2,254 0,0020 0,027 0,027

Stage 5 1,013 0,0020 0,001 0,010

Table 190: Emission factors for diesel engines 80 - 130 kW.


AG1 10,193 0,0030 1,578 1,623

AG2 12,392 0,0024 1,183 0,885

Stage 1 6,555 0,0020 0,210 0,226

Stage 2 4,833 0,0014 0,146 0,162

Stage 3a 5,860 0,0010 0,077 0,079

Stage 3b 4,347 0,0010 0,033 0,034

Stage 4 2,254 0,0010 0,027 0,027

Stage 4 SCR 2,254 0,0010 0,027 0,027

Stage 5 1,013 0,0010 0,001 0,010

Table 191: Emission factors for diesel engines >130 kW.


AG1 10,193 0,0030 1,578 1,623

AG2 12,392 0,0024 1,183 0,885

Stage 1 6,555 0,0020 0,210 0,226

Stage 2 4,833 0,0014 0,146 0,162

Stage 3a 5,860 0,0010 0,077 0,079

Stage 3b 2,635 0,0010 0,033 0,034

Stage 4 2,254 0,0010 0,027 0,027

Stage 4 SCR 2,254 0,0010 0,027 0,027

Stage 5 1,013 0,0010 0,001 0,010



Table 192: Emission factors for 4-stroke-petrol engines.


AG1 3,070 0,0019 16,166 0,025

AG2 4,110 0,0017 12,940 0,025

Stage 1 4,490 0,0016 12,360 0,025

Stage 2 4,490 0,0018 11,933 0,025

Stage 3a 4,490 0,0018 11,015 0,025

Stage 3b 4,490 0,0018 11,015 0,025

Stage 4 4,490 0,0018 11,015 0,025

Stage 4 SCR 4,490 0,0018 11,015 0,025

Stage 5 4,490 0,0018 11,017 0,025

Table 193: Emission factors for 2-stroke-petrol engines.


AG1 1,035 0,0017 247,797 0,439

AG2 1,135 0,0015 174,290 0,291

Stage 1 1,675 0,0013 164,637 0,291

Stage 2 1,395 0,0012 50,490 0,291

Stage 3a 1,395 0,0004 50,490 0,291

Stage 3b 1,395 0,0004 50,490 0,291

Stage 4 1,395 0,0004 50,490 0,291

Stage 4 SCR 1,395 0,0004 50,490 0,291

Stage 5 1,395 0,0004 50,490 0,291

Exhaust emissions ‒ PM

Emission factors used for (PM2.5 and PM10) include the condensable component. As condensa-ble means "condensing on the filter at <52 °C", this definition is exactly in line with the PM measurement rules on the emission test benches for road vehicles and NRMM. Also see Table “Information on PM emission factors” in the Annex (chapter 12.3).

Non-exhaust emissions ‒ PM From the submission 2019 onwards non-exhaust emissions from road resuspension are not re-ported respectively included in the reported PM figures any more. This is now consistent with the reporting of PM non-exhaust emissions in 1.A.3.b Road Transport.

Regarding non-exhaust emissions, the EMEP/EEA 2016 Guidebook puts a focus on primary particles. Following, road resuspension of previously deposited material, is not being reported any longer from the submission 2017 onwards, but can be provided when needed.

No information is given in the EMEP/EEA Guidebook 2016, if the condensable fraction is rele-vant in non-exhaust emission factors (PM2.5 and PM10). Also see Table “Information on PM emission factors” in the Annex (chapter 12.3).



Activity data and implied emission factors of 1.A.2.g.vii are presented below. Activities of mobile machinery in 1.A.2.g.vii also contain commercially/institutionally used machinery. They could not be split into commercial/institutional and non-commercial/non-institutional use due to a lack of data.

Table 194: Activities and Implied emission factors for NEC gases for 1.A.2.g.7 Off-road – Industry: 1990–2018.

Year Activity IEF SO2 IEF NOx IEF NMVOC IEF NH3 IEF PM2.5

[TJ] [t/PJ]

1990 3,448 59.5 878.5 149.9 0.32 152.2

1991 3,897 59.5 880.4 149.4 0.32 151.2

1992 4,127 59.5 882.1 149.0 0.32 150.2

1993 4,340 59.5 883.3 148.7 0.32 149.6

1994 4,555 50.4 897.2 146.4 0.31 145.4

1995 4,821 18.6 921.3 142.3 0.31 138.3

1996 6,008 18.6 956.6 136.2 0.30 127.7

1997 5,663 18.6 984.0 132.0 0.29 119.9

1998 6,660 18.6 1,004.3 128.6 0.28 114.2

1999 6,353 16.3 1,018.4 126.3 0.28 109.8

2000 7,426 16.3 1,027.9 124.4 0.28 106.6

2001 6,980 16.3 1,032.5 123.4 0.27 104.6

2002 6,793 16.3 1,023.1 121.0 0.27 102.2

2003 7,241 16.3 962.3 108.8 0.26 92.1

2004 7,965 2.4 861.6 90.5 0.25 77.4

2005 11,017 2.4 736.8 67.7 0.23 60.5

2006 13,683 2.4 637.0 50.6 0.21 46.0

2007 14,826 0.5 590.2 40.6 0.19 37.1

2008 16,351 0.5 572.8 34.0 0.18 31.2

2009 15,988 0.5 562.0 30.3 0.17 27.5

2010 15,334 0.5 556.4 28.5 0.17 25.6

2011 15,412 0.5 558.7 26.8 0.16 23.6

2012 15,971 0.5 544.4 24.3 0.15 20.7

2013 16,063 0.5 513.3 21.6 0.15 17.8

2014 15,737 0.5 489.4 19.9 0.14 15.9

2015 15,337 0.5 466.8 18.3 0.14 14.2

2016 15,439 0.5 435.3 16.2 0.14 12.1

2017 16,205 0.5 392.6 13.9 0.13 9.8

2018 17,353 0.5 355.2 11.8 0.13 7.8



No recalculations have been made in this year’s submission.




A new study is planned to be commissioned in 2020. Parameters such as operating times, vehi-cle stock (focus e-vehicles) and emission factors for the off road sector will be updated.

3.2.7.2 NFR 1.A.3.c Railways


The applied methodology is described in the subchapter on mobile sources of 1.A.2.g.vii (see Chapter 3.2.7.1).

Activity Data

In this category emissions from diesel railcars and steam engines are considered. Activities used for estimating the emissions of 1.A.3.c Railways are presented below. Activities include liquid fuels (diesel and biodiesel) as well as solid fuels (coal) yearly taken from the national en-ergy balance.

Table 195: Activities for 1.A.3.c Railways: 1990–2018.

Year Liquid fuels [TJ]

Solid fuels [TJ]

1990 2,311 69.7

1991 2,120 63.4

1992 2,099 66.2

1993 2,051 59.8

1994 2,071 58.8

1995 1,926 61.0

1996 1,736 60.8

1997 1,753 34.6

1998 1,730 30.8

1999 1,788 29.8

2000 1,788 26.0

2001 1,728 18.2

2002 1,869 20.2

2003 1,880 15.8

2004 1,880 6.1

2005 2,189 5.2

2006 2,137 5.8

2007 2,125 5.5

2008 2,123 4.8

2009 2,078 6.3

2010 2,035 4.6

2011 1,710 4.6

2012 1,760 4.9

2013 1,621 4.9



Year Liquid fuels [TJ]

Solid fuels [TJ]

2014 1,695 4.9

2015 1,520 4.84

2016 1,576 4.87

2017 1,638 4.93

2018 1,304 4.68

1990–2018 -44% -93%

Emission Factors

Emission factors were taken from (HAUSBERGER 2006). Implied emission factors of 1.A.3.c Rail-ways are listed in the following table.

Table 196: Activities and Implied emission factors for NEC gases for 1.A.3.c Railways: 1990–2018.


1990 2,380.2 110.8 764.1 153.4 0.3 250.2 1991 2,182.9 110.3 766.6 153.0 0.3 255.0 1992 2,165.2 113.0 768.8 152.7 0.3 255.1 1993 2,110.6 109.1 771.9 152.0 0.3 255.2 1994 2,129.4 107.9 778.7 151.1 0.3 252.5 1995 1,986.9 104.3 784.9 150.6 0.3 256.8 1996 1,796.4 83.2 790.9 150.2 0.3 264.2 1997 1,787.8 57.6 800.8 147.4 0.3 258.3 1998 1,761.1 54.3 808.3 146.3 0.3 257.1 1999 1,818.3 52.4 816.3 145.1 0.3 251.8 2000 1,814.5 48.8 825.1 143.8 0.3 249.0 2001 1,746.2 41.9 835.2 142.1 0.3 248.5 2002 1,889.4 42.4 842.6 138.2 0.3 235.9 2003 1,895.6 38.2 838.4 135.6 0.3 232.6 2004 1,885.8 29.2 835.0 132.5 0.2 229.0 2005 2,194.0 27.7 826.1 127.8 0.2 211.1 2006 2,143.2 28.5 820.6 123.7 0.2 207.2 2007 2,131.0 28.3 799.7 115.9 0.2 196.6 2008 2,127.4 27.7 779.1 107.9 0.2 185.5 2009 2,084.6 29.1 760.8 100.1 0.2 176.0 2010 2,039.3 27.8 739.8 91.8 0.2 165.9 2011 1,714.8 28.6 718.3 83.8 0.2 168.9 2012 1,764.6 28.7 696.4 79.5 0.2 159.6 2013 1,626.0 29.2 663.4 72.1 0.2 156.3 2014 1,700.1 29.0 632.5 64.6 0.2 141.1 2015 1,525.0 29.6 611.4 61.2 0.2 147.0 2016 1,581.2 29.3 599.8 60.4 0.2 142.9 2017 1,642.5 29.2 576.4 56.8 0.2 135.2 2018 1,308.4 30.2 564.0 55.4 0.2 158.2





The adjustment of the CH4 emission factors to the EMEP/EEA Guidebook 2019 led to a slight change of the NMVOC emissions over the whole time series

Adjustment of energy quantities to the energy balance from 2005 onwards.

Category-specific Planned Improvements The activity data are taken from the national energy balance that is provided by the national sta-tistical office (‘Statistik Austria’). The changes (between 2004-2005 and 2010–2011) will be ana-lyzed together with Statistik Austria in 2020 according to our sectoral improvement plan. If the changes are caused by the survey design or the method used by the statistical office, a national bottom up study will be carried out (The results could be used to improve the national energy balance).

3.2.7.3 NFR 1.A.3.d Navigation


Austria uses the bottom-up model GEORG (HAUSBERGER 2000) to calculate fuel consumption in navigation which is made up of freight transport activities on the River Danube and passenger transport on rivers and lakes in Austria. Passenger transport is conducted with passenger ships, private motor boats and sailing boats. The inland navigation fleet (stock) was obtained from reg-istration statistics from provincial governments, the average yearly operating time as well as the average fuel consumption per hour from questionnaires to fleet operators and/or manufacturers’ data. Statistical data (tkm) for freight activities on the River Danube were obtained from (STATISTIK AUSTRIA 2019a). Additionally, fuel consumption for working boats is taken into ac-count in the national fuel consumption of navigation.

Emissions are calculated bottom-up with the model GEORG. The inland navigation fleet (stock) was obtained from registration statistics from provincial governments, the average yearly oper-ating time as well as the average fuel consumption per hour from questionnaires to fleet opera-tors and/or manufacturers’ data. Methodological issues of the model GEORG are described in the subchapter on mobile sources of 1.A.2.g.vii (see Chapter 3.2.7.1).

Activity Data

This sector includes emissions from fuels used by vessels of all flags that depart and arrive in Austria (excludes fishing) and emissions from international inland waterways, including emis-sions from journeys that depart in Austria and arrive in a different country. Activities used for es-timating the emissions of 1.A.3.d Navigation are presented in Table 190. Activities include liquid fuels (diesel, gasoline and biofuels).

Emission Factors

Emission factors were taken from (HAUSBERGER 2006). Implied emission factors of 1.A.3.d Nav-igation are listed below.



Table 197: Activities and Implied emission factors for NEC gases for 1.A.3.d Navigation: 1990–2018.

Year Activities IEF SO2 IEF NOx IEF NMVOC IEF NH3 IEF PM2.5

[TJ] [t/PJ]

1990 863 52.4 673.9 687.2 0.2 152.2

1991 780 51.6 661.1 742.5 0.2 150.9

1992 763 51.4 661.3 753.9 0.2 149.5

1993 769 51.5 664.8 747.4 0.2 148.8

1994 922 52.7 689.2 641.1 0.2 151.6

1995 1,016 44.6 704.6 585.8 0.2 152.0

1996 1,037 21.2 713.4 567.2 0.2 150.7

1997 1,029 21.2 719.8 560.9 0.2 148.9

1998 1,108 21.4 732.9 522.1 0.2 148.4

1999 1,085 21.3 739.4 520.7 0.2 146.0

2000 1,172 21.5 753.3 484.1 0.2 145.2

2001 1,218 21.6 765.1 463.3 0.2 143.4

2002 1,336 21.7 778.8 424.7 0.2 139.2

2003 1,095 21.4 772.4 477.6 0.2 131.2

2004 1,314 21.2 794.5 406.7 0.2 127.7

2005 1,290 21.2 793.7 394.7 0.2 119.1

2006 1,145 21.0 786.2 410.1 0.2 109.2

2007 1,216 20.9 781.8 376.5 0.2 97.2

2008 1,116 20.7 758.3 381.0 0.2 86.0

2009 966 20.3 731.5 401.4 0.2 74.3

2010 1,116 20.7 725.7 346.4 0.2 69.0

2011 1,009 20.5 702.6 352.7 0.2 61.7

2012 1,035 20.6 693.4 329.8 0.2 58.9

2013 1,098 20.8 687.1 302.0 0.2 56.6

2014 1,021 20.6 673.9 301.2 0.2 53.7

2015 867 20.2 653.2 319.7 0.2 50.3

2016 927 20.4 648.9 292.1 0.2 48.1

2017 949 20.5 635.2 275.5 0.2 45.2

2018 730 19.7 608.3 314.3 0.2 43.0



Harmonization of CRF and IEA data

In 2013 the ERT detected inconsistencies of fuel consumption data of domestic aviation and domestic navigation between the CRF tables and the IEA data (ICR 2013). In response to that it was explained that Austria uses a bottom-up approach to estimate fuel consumption whilst IEA relies on top-down approach based on fuel consumption statistics reported by Statistics Austria.



After having discussed this issue with Statistics Austria an Explanatory Note (30/09/2013) has been compiled by Statistics Austria declaring that a regular adoption of inventory data for the split between national and international fuel consumption in civil aviation and navigation in the national statistics will be adopted in the future, as far as the data can be submitted in time (early November).

As part of regular QA/QC the energy split between national and international navigation is pro-vided to Statistics Austria for the IEA statistics based on the bottom up model used to calculate the annual emission inventory.

Completeness In response to a question raised by the ERT (ICR 2013) it was explained that emissions of ground activities at domestic harbors are also included, even if they are not separately reported under 1.A.3.d Navigation. This can be assured as Austria reports emissions from total fuel sold from the energy balance.

The approach in the Austrian inventory is as follows: After calculating fuel consumption for in-land road transport and off-road transport using a bottom-up approach (NEMO, GEORG), the sum of this fuel used is compared with the total fuel sold from the national energy balance (for details see 1.A.3.b Road Transport). The difference is then allocated to fuel export, which in-cludes fuel consumption for ground activities at airports and harbors as well, including fuel con-sumption by unregistered vehicles. As the fuel consumption reported under fuel export is in-cluded in the national totals110, an underestimation of emissions can be excluded. Category-specific Recalculations

The adjustment of the CH4 emission factors to the EMEP/EEAGuidebook 2019 led to a slight change of the NMVOC emissions over the whole time series Category-specific Planned Improvements


3.2.7.4 NFR 1.A.4.a.2 Commercial/institutional – mobile sources

Currently there is neither a statistical basis nor any new study on NRMM which would enable Austria to report emissions from mobile sources of 1.A.4.a.2 Commercial/institutional separate-ly. Commercial and institutional NRMM are reported as IE and are included in 1.A.2.g.vii Indus-try and 1.A.4.c.2 Agriculture and Forestry.

3.2.7.5 NFR 1.A.4.b.2 Household and gardening – mobile sources

In addition to NRMM used in household and gardening, this category contains mobile machin-ery such as ski slope machineries, skidoos or mowers.


The applied methodology is described in the subchapter on mobile sources of 1.A.2.g.vii (see Chapter 3.2.7.1). 110 GHG emissions from fuel export are included in 1.A.3.b and are presented separately in Table 66 (Chapter 3.2.12.2)



Activity Data

In addition to vehicles used in household and gardening this category contains ski slope ma-chineries and snow vehicles. Activities used for estimating emissions of 1.A.4.b.2 Household and gardening – mobile sources are presented in Table 191. Activities include liquid fuels (die-sel, gasoline and biofuels).

Emission Factors

Details concerning emission factors for mobile off-road sources are described in the subchapter on mobile sources of 1.A.2.g.vii (see Chapter 3.2.7.1). However, for mobile machinery in households and gardening the previous set of EFs of diesel engines (prior to the update 2017) has been taken as shown in the IIR 2017. EFs of petrol engines have not been updated by the mentioned update. Implied emission factors of 1.A.4.b.2 Household and gardening – mobile sources are listed below.

Table 198: Activities and Implied emission factors for NEC gases for 1.A.4.b.ii Off-road – Household and gardening: 1990–2018.


[TJ] [t/PJ]

1990 1,916 29.5 419.2 2,379.6 0.2 70.2

1991 1,920 29.5 420.8 2,382.2 0.2 69.2

1992 1,937 29.6 424.5 2,373.4 0.2 68.7

1993 1,948 29.7 427.8 2,366.8 0.2 68.0

1994 1,937 25.5 433.4 2,337.6 0.2 65.9

1995 1,944 11.1 450.5 2,248.9 0.2 63.6

1996 1,923 11.1 460.6 2,189.3 0.1 60.5

1997 1,905 11.1 469.6 2,124.8 0.1 58.2

1998 1,889 11.1 478.9 2,056.5 0.1 55.9

1999 1,885 10.0 487.7 1,990.6 0.1 53.6

2000 1,885 10.0 497.4 1,928.3 0.1 51.4

2001 1,887 10.0 506.4 1,880.0 0.1 49.2

2002 1,885 10.0 509.4 1,846.0 0.1 46.2

2003 1,879 10.0 506.4 1,833.0 0.1 42.7

2004 1,867 2.4 499.2 1,758.4 0.1 39.3

2005 1,844 2.4 490.0 1,625.7 0.1 36.2

2006 1,820 2.4 480.2 1,494.7 0.1 33.2

2007 1,797 0.5 466.0 1,355.4 0.1 30.4

2008 1,767 0.5 449.6 1,216.9 0.1 27.8

2009 1,744 0.5 429.9 1,078.9 0.1 25.2

2010 1,727 0.5 406.7 955.5 0.1 22.7

2011 1,718 0.5 381.5 856.4 0.1 20.4

2012 1,712 0.5 355.8 784.6 0.1 18.2

2013 1,715 0.5 330.2 753.8 0.1 16.0

2014 1,729 0.5 305.5 743.6 0.1 14.0

2015 1,737 0.5 282.8 740.9 0.1 12.3




[TJ] [t/PJ]

2016 1,739 0.5 262.2 744.2 0.1 10.8

2017 1,747 0.5 241.4 743.0 0.1 9.5

2018 1,751 0.5 222.2 742.4 0 8.5


Category-specific recalculations

The adjustment of the CH4 emission factors to the EMEP/EEA Guidebook 2019led to a slight change of the NMVOC emissions over the whole time series.



3.2.7.6 NFR 1.A.4.c.2 Agriculture and forestry – mobile sources

In this category emissions from NRMM used in agriculture and forestry (mainly tractors) are considered.


The general methodology applied is described in the subchapter on mobile sources of 1.A.2.g.vii (see Chapter 3.2.7.1). For the submission 2018 the growth indicator "grain harvest" was re-analysed. A comprehensive analysis of key figures in agriculture (STATISTIK AUSTRIA 2019c) has shown that production data and developments in agricultural areas often counteract each other. A pure usage of production data for the calibration of the annual operating hours, as well as the direct allocation of the decrease in area to operating hours did not appear to be suf-ficient any more. Following improvements have been implemented in the model GEORG of the Graz University of Techanology: Fixed tractor operating hours are following the decrease in agricultural area (data available

for base year 2005 with 90 fixed operating hours per tractor per year). Variable tractor operating hours are still calibrated with the growth indicator “grain harvest”

(data available for base year 2005 with 70 variable operating hours per tractor per year). From 2005, a slight increase in efficiency of tractor usage in relation to area and production of

around 0.5 % per year was assumed.

Activity Data

In this category emissions from off-road machinery in agriculture and forestry (mainly tractors) are considered. Activities of mobile machinery in 1.A.4.c.2 also contain commercially/institutionally used machinery. They could not be split into commercial/institutional and non-commercial/non-institutional use due to a lack of data.

Activities used for estimating emissions of 1.A.4.c.2 Agriculture and Forestry – mobile sources are presented in Table 192. Activities include liquid fuels (diesel, gasoline and biofuels).



Emission Factors

Details concerning emission factors for mobile off-road sources are described in the subchapter on mobile sources of 1.A.2.g.vii (see Chapter 3.2.7.1). Implied emission factors of 1.A.4.c.2 Ag-riculture and Forestry – mobile sources are presented below.

Table 199: Activities and Implied emission factors for NEC gases for 1.A.4.c.ii Off-road Vehicles and Other Machinery – Agriculture/Forestry/Fishing: 1990–2018.


[TJ] [t/PJ]

1990 10,377 57.9 907.7 380.2 0.4 198.4

1991 10,339 58.2 915.1 332.2 0.5 196.6

1992 10,429 58.2 917.5 338.0 0.5 194.9

1993 10,480 58.2 920.9 336.0 0.5 192.9

1994 10,569 49.2 921.1 353.8 0.5 189.8

1995 10,115 18.3 922.2 350.2 0.4 185.4

1996 10,520 18.3 923.7 349.7 0.4 180.9

1997 11,047 18.3 927.2 331.7 0.4 176.3

1998 10,847 18.3 928.8 322.7 0.4 172.2

1999 10,950 16.0 930.4 316.7 0.4 168.7

2000 10,621 16.0 931.1 309.6 0.4 165.7

2001 10,947 16.0 932.4 302.8 0.4 163.1

2002 10,900 16.0 916.7 309.1 0.4 157.3

2003 10,472 16.0 888.6 327.3 0.4 149.5

2004 10,775 2.4 865.3 299.8 0.4 141.2

2005 11,451 2.4 842.6 268.7 0.4 133.1

2006 11,370 2.4 819.0 269.4 0.4 126.3

2007 11,312 0.5 795.9 262.5 0.4 118.6

2008 12,252 0.5 782.3 231.2 0.3 110.2

2009 11,219 0.5 771.7 196.3 0.3 101.8

2010 10,926 0.5 756.5 186.9 0.3 94.3

2011 11,845 0.5 744.9 166.1 0.3 86.6

2012 10,936 0.5 731.6 156.7 0.3 79.7

2013 10,587 0.5 711.1 144.7 0.3 72.8

2014 11,698 0.5 690.1 125.5 0.3 65.9

2015 10,826 0.5 665.7 124.6 0.3 60.8

2016 11,642 0.5 641.2 110.3 0.2 54.8

2017 10,805 0.5 614.8 112.6 0.2 50.7

2018 10,898 0.5 588.7 111.5 0.2 46.7




Category-specific recalculations

The adjustment of the CH4 emission factors to the EMEP/EEA Guidebook 2019 led to a slight change of the NMVOC emissions over the whole time series.



3.2.7.7 NFR 1.A.5.b Other – mobile

In this category emissions of NRMM used for military transport (off-road and aviation) are re-ported.

Military Off-Road Transport (ground operations)


The applied methodology is described in the subchapter on mobile sources of 1.A.2.g.vii (see Chapter 3.2.7.1).

Activity Data

Emission estimates for military activities were taken from (HAUSBERGER 2000). Information on the fleet composition was taken from official data presented in the internet as no other data were available. Also no information on the road performance of military vehicles was available, that’s why emission estimates only present rough estimations, which were obtained making the following assumptions: for passenger cars and motorcycles the yearly road performance as cal-culated for civil cars was used. The yearly road performance for such vehicles was estimated to be 30 h/year (as a lot of vehicles are old and many are assumed not to be in actual use any-more).

Activities used for estimating the emissions of 1.A.5.b Military Off-road are presented below.

Emission Factors

For tanks and other special military vehicles the emission factors for diesel engines > 80 kW was used (for these vehicles a power of 300 kW was assumed). Details concerning emission factors for mobile off-road sources are described in the subchapter on mobile sources of 3.2.7 Other mobile sources – Off Road.


Military Aviation


For the years 1990–1999 fuel consumption for military flights was reported by the Ministry of Defence. For the years from 2000 onwards the trend has been extrapolated. The calculation of emissions from military aviation does not distinguish between LTO and cruise.



Activity Data

Activities used for estimating the emissions of Military Aviation (kerosene) and Military Off-Road Transport with diesel are presented in the following table.

Table 200: Activities from 1.A.5.b Other – mobile: 1990–2018.

Year Kerosene [TJ]

Diesel [TJ]

1990 452 29

1991 481 29

1992 434 29

1993 513 28

1994 543 28

1995 419 28

1996 506 28

1997 482 28

1998 555 28

1999 544 27

2000 533 27

2001 541 27

2002 549 27

2003 556 27

2004 564 27

2005 572 27

2006 580 27

2007 587 27

2008 595 27

2009 603 27

2010 611 27

2011 618 27

2012 626 27

2013 634 27

2014 642 27

2015 650 27

2016 657 27

2017 664 27

2018 672 27

1990–2018 49% -6%



Emission Factors For the years from 2000 onwards, emissions for military flights have been calculated with IEFs from the year 2000 taken from (KALIVODA/KUDRNA 2002).

Table 201: IEF for the year 2000

IEFs

2000 [t] [kg/t fuel]

Fuel 13 613

SO2 13.68 1.0

NOx 66 4.9

NH3 0.08 0.0

VOC_HC 15 1.1

NMVOC 13.25 1.0

PM2.5 13 1.0

CO 258 18.9


No recalculations have been made in this year’s submission.

3.2.8 Emission factors for heavy metals, POPs and PM used in NFR 1.A.3 Transport

In the following chapter the emission factors for heavy metals and POPs used in NFR 1.A.3 are described. For 1.A.3.a Civil Aviation and 1.A.5.b Military (Aviation) POPs emissions are not es-timated (NE).

3.2.8.1 Heavy metals

As can be seen in Table 82, the HM content of lighter oil products in Austria are below the de-tection limit. For Cd, Hg and for Pb from 1995 onwards 50% of the detection limit was used as emission factor for all years.

For Pb emission factors for gasoline before 1995 were calculated from the legal content limit for the different types of gasoline and the amounts sold of the different types in the respective year. Furthermore, it was considered that according to the CORINAIR 1997 Guidebook the emission rate for conventional engines is 75% and for engines with catalyst 40% (the type of fuel used in the different engine types was also considered).

The production and import of leaded gasoline has been prohibited in Austria since 1993. Earlier emission estimates are based on a lead content of 0.56 g Pb/litre for aviation gasoline. From 1996 on a lead content of 0,1 mg/GJ has been estimated for gasoline due to the assumed use of lead additives for old non-catalyst vehicles and that a lead content of 0.02 mg/GJ has been assumed for diesel oil and kerosene.

The same emission factors were also used for mobile combustion in Categories NFR 1.A.2, NFR 1.A.4 and NFR 1.A.5.b Military (Off-road sources).

For coal fired steam locomotives in NFR 1.A.3.c the emission factor for uncontrolled coal com-bustion from the CORINAIR 1997 Guidebook was used.



Table 202: HM emission factors for Sector 1.A.3 Transport and SNAP 08 Off-Road Machinery.

EF [mg/GJ] Cd Hg Pb

Diesel, kerosene, gasoline, aviation gasoline (see also following table)

0.02 0.01 0.02

Coal (railways) 5.4 10.7 89

Automobile tyre- and break-wear: passenger cars, motorcycles

0.5 – –

Automobile tyre- and break-wear: LDV and HDV 5.0 – –

Table 203: Pb emission factors for gasoline for Sector 1.A.3 Transport and SNAP 08 Off-Road Machinery.

Pb EF [mg/GJ] 1985 1990 1995

gasoline (conventional) 2 200 2 060 0.1

gasoline (catalyst) 130 130 0.1

gasoline type jet fuel 23 990 15 915 0.1

In this year’s submission, Pb emissions from Tyre and Break wear are reported for the first time. Pb emissios were integrated in themodel NEMO using the mean values of the emission factors contained in the EMEP/EEA air pollutant emission inventory guidebook 2019.

The result contains shares of lead emissions for road traffic according to the guidebook for the components: Engine, Liquids, tire wear, brake abrasion

Table 204: Pb emission factors for 1A3bvi Tyre and Break wear (SNAP 070700X7A, 070700X7B, 070700X7C)

Pb EF [mg/1000 Vehicle km] 1985

2Wheelers 486.7

Passenger cars 47.4

LDV & HDV 108.5



3.2.8.2 POPs emissions

In the following the emission factors for POPs (PAH, Dioxin, HCB and PCB) used in NFR 1.A.3 and in the off-road transport are described.111

PAH emission factors

For the 2016 submission the emission factors for 1.A.3.b Road Transport were updated in the model NEMO for the four PAHs relevant for the UNECE POPs protocol: indeno(1,2,3-cd)pyrene benzo(k)fluoranthene benzo(b)fluoranthene benzo(a)pyrene

According to the EMEP/EEA Guidebook 2013 (EEA 2013) specific exhaust emission factors were taken for each vehicle category and emission class given in [µg/km]. The non-exhaust emission factors (abrasion and suspension) were also taken from (EEA 2013) and implemented in the model NEMO as ratio factors of TSP non-exhaust (from tires and brake) in ppm (mass re-lated). These emission factors are calculated in NEMO according to the Tier 2 methodology (HAUSBERGER et al. 2015c) via relationship factors from the tyre and brake TSP emission values.

For estimating PAK emissions from mobile off-road sources in NFR 1.A.2, NFR 1.A.3.c, NFR 1.A.3.d, NFR 1.A.4 and NFR 1.A.5.b trimmed averages from emission factors in (UBA BERLIN 1998), (SCHEIDL 1996) and (ORTHOFER & VESSELY 1990) as well as measurements of emissions of a tractor engine by FTU (FTU 2000) were applied. For diesel fuelled mobile off-road sources the HDV emission factor was taken; for gasoline driven mobile sources in 1.A.3.d and 1.A.4.c (agriculture) the PC gasoline value; for gasoline fuelled mobile sources in 1.A.2, 1.A.4.b and 1.A.4.c.2 (forestry) the motorcycles <50 ccm value was taken.

For coal fired steam locomotives in NFR 1.A.3.c the same emission factor as for 1.A.4.b – stoves were used.

Table 205: POP emission factors for Sector SNAP 08 Off-Road Machinery.

PCDD/F EF [µgTE/GJ] PAK4 [mg/GJ]

Passenger cars gasoline 0.046 5.3

PC. gasoline with catalyst 0.0012 0.32

Passenger cars diesel 0.0007 6.4

LDV 0.0007 6.4

HDV 0.0055 6.4

Motorcycles < 50 ccm 0.0031 21

Motorcycles < 50 ccm with catalyst 0.0012 2.1

Motorcycles > 50 ccm 0.0031 33

Coal fired steam locomotives 0.38 0.085

111 Emissions from off-road machinery are reported under 1.A.2.g.vii (machinery in industry), 1.A.4.b.2 (machinery in

household and gardening), 1.A.4.c.2 (machinery in agriculture/forestry/fishing) and 1.A.5.b. (Military mobile sources).



Dioxin emissions

Dioxin emission factors are presented in Table 197 and based on findings from (HÜBNER 2001).

HCB emissions

HCB emissions were calculated on the basis of dioxin emissions and assuming a factor of 200 (HÜBNER 2001).

PCB emission factors

PCB emissions from 1.A.3.b Road Transport were calculated and reported for the first time in the current submission. For the calculation of PCB emissions in the model NEMO specific emis-sion factors were taken from (EEA 2013) for each vehicle category and emission class given in [picograms/km]. Due to the low emission factors given in the guidebook, the calculated PCB emissions from 1.A.3.b Road Transport are a minor source (HAUSBERGER et al. 2015c).

PCB emissions from mobile off-road machinery in NFR 1.A.2, NFR 1.A.3.c, NFR 1.A.3.d, NFR 1.A.4 and NFR 1.A.5 were calculated for the first time in the current submission. Since no calcu-lation method or values for these emissions are given in the literature, for diesel machines they were derived from truck emissions from road transport (approach: PCB emissions related to en-gine work). For gasoline-powered equipment, motorcycles have been used (approach: PCB emissions as a percentage of the HC emissions) (HAUSBERGER et al. 2015c).

3.2.8.3 Implied emission factors per subcategory

NFR 1.A.3.a Civil Aviation – LTO

Emissions of lead are only relevant for aviation gasoline (only used for national VFR flights) and have significantly dropped between 1994 and 1995 in consequence of a prohibition of the pro-duction and import of leaded gasoline in Austria (also see chapter 3.2.8.1).

Table 206: Activities and Implied emission factors for heavy metals for 1.A.3.a.ii Civil Aviation (domestic LTO + international LTO): 1990–2018.

Year Activity IEF Cd IEF Hg IEF Pb

[TJ] [kg/PJ]

1990 1,481 0.02 0.01 1,105.1

1991 1,671 0.02 0.01 1,009.3

1992 1,861 0.02 0.01 933.8

1993 2,051 0.02 0.01 873.1

1994 2,242 0.02 0.01 823.3

1995 2,405 0.02 0.01 0.02

1996 2,577 0.02 0.01 0.02

1997 2,764 0.02 0.01 0.02

1998 2,948 0.02 0.01 0.02

1999 3,018 0.02 0.01 0.02

2000 3,239 0.02 0.01 0.02

2001 3,038 0.02 0.01 0.02

2002 3,532 0.02 0.01 0.02




[TJ] [kg/PJ]

2003 3,670 0.02 0.01 0.02

2004 4,323 0.02 0.01 0.02

2005 4,055 0.02 0.01 0.02

2006 4,067 0.02 0.01 0.02

2007 4,372 0.02 0.01 0.02

2008 4,470 0.02 0.01 0.02

2009 4,115 0.02 0.01 0.02

2010 4,181 0.02 0.01 0.02

2011 4,726 0.02 0.01 0.02

2012 4,484 0.02 0.01 0.02

2013 4,375 0.02 0.01 0.02

2014 4,390 0.02 0.01 0.02

2015 4,624 0.02 0.01 0.02

2016 4,744 0.02 0.01 0.05

2017 4,555 0.02 0.01 0.06

2018 4,955 0.02 0.01 0.06

Memo Item 1.A.3.a Civil Aviation – Cruise

As aviation gasoline is only used for domestic VFR flights the significant drop of lead emissions in the 90ies is not visible in the cruise emissions. PAH, Dioxin, HCB and PCB emissions are not estimated.

Table 207: Activities and Implied emission factors for heavy metals for International Bunkers (domestic + international cruise traffic): 1990–2018.


[TJ] [kg/PJ]

1990 11,138 0.02 0.01 0.02

1991 12,508 0.02 0.01 0.02

1992 13,543 0.02 0.01 0.02

1993 14,289 0.02 0.01 0.02

1994 14,802 0.02 0.01 0.02

1995 16,638 0.02 0.01 0.02

1996 18,458 0.02 0.01 0.02

1997 19,181 0.02 0.01 0.02 1998 19,814 0.02 0.01 0.02

1999 19,293 0.02 0.01 0.02

2000 20,977 0.02 0.01 0.02

2001 20,471 0.02 0.01 0.02

2002 18,488 0.02 0.01 0.02

2003 17,147 0.02 0.01 0.02

2004 20,255 0.02 0.01 0.02

2005 23,784 0.02 0.01 0.02




2006 25,064 0.02 0.01 0.02

2007 26,529 0.02 0.01 0.02

2008 26,475 0.02 0.01 0.02

2009 22,820 0.02 0.01 0.02

2010 24,846 0.02 0.01 0.02

2011 25,907 0.02 0.01 0.02

2012 24,739 0.02 0.01 0.02

2013 23,512 0.02 0.01 0.02

2014 23,469 0.02 0.01 0.02

2015 25,300 0.02 0.01 0.02

2016 27,860 0.02 0.01 0.02

2017 26,898 0.02 0.01 0.02

2018 30,451 0.02 0.01 0.02 NFR 1.A.3.b Road Transport

Emissions of lead are only relevant for gasoline and have significantly dropped in the mid 90ies as a result of unleaded gasoline introduction.

Table 208: Activities and Implied emission factors for heavy metals and POPs for 1.A.3.b Road Transport: 1990–2018.

Year Activity [TJ]

IEF Cd [kg/PJ]

IEF Hg [kg/PJ]

IEF Pb [kg/PJ]

IEF PAH [kg/PJ]

IEF Diox [g/PJ]

IEF HCB [g/PJ]

IEF PCB [g/PJ]

1990 176,826 0.09 0.01 1,004.63 1.49 0.02 4.65 0.002

1991 196,386 0.09 0.01 749.19 1.50 0.02 4.20 0.002

1992 196,215 0.09 0.01 520.73 1.53 0.02 3.67 0.002

1993 198,243 0.09 0.01 336.49 1.56 0.02 3.16 0.002

1994 199,009 0.09 0.01 201.73 1.62 0.01 2.75 0.002

1995 202,791 0.09 0.01 15.59 1.67 0.01 2.36 0.002

1996 224,095 0.09 0.01 14.58 1.64 0.01 1.92 0.002

1997 210,964 0.09 0.01 15.83 1.66 0.01 1.69 0.003

1998 237,523 0.09 0.01 14.51 1.58 0.01 1.45 0.002

1999 229,403 0.09 0.01 15.47 1.53 0.01 1.27 0.003

2000 241,747 0.09 0.01 15.05 1.44 0.01 1.11 0.003

2001 259,856 0.09 0.01 14.27 1.36 0.01 1.00 0.003

2002 288,170 0.08 0.01 13.24 1.29 0.00 0.91 0.003

2003 311,792 0.08 0.01 12.57 1.23 0.00 0.84 0.003

2004 318,769 0.08 0.01 12.50 1.19 0.00 0.78 0.003

2005 325,692 0.08 0.01 12.30 1.15 0.00 0.80 0.003

2006 313,467 0.08 0.01 13.03 1.16 0.00 0.85 0.003

2007 317,097 0.08 0.01 13.03 1.12 0.00 0.84 0.003

2008 299,955 0.08 0.01 13.43 1.09 0.00 0.90 0.003

2009 295,039 0.08 0.01 13.48 1.06 0.00 0.99 0.003

2010 306,694 0.08 0.01 13.17 1.04 0.00 1.00 0.003

2011 296,496 0.08 0.01 13.89 1.03 0.00 0.99 0.002



Year Activity [TJ]

IEF Cd [kg/PJ]

IEF Hg [kg/PJ]

IEF Pb [kg/PJ]

IEF PAH [kg/PJ]

IEF Diox [g/PJ]

IEF HCB [g/PJ]

IEF PCB [g/PJ]

2012 296,250 0.08 0.01 13.87 1.01 0.01 1.01 0.002

2013 309,917 0.08 0.01 13.40 1.01 0.01 1.00 0.002

2014 302,483 0.08 0.01 14.11 1.01 0.01 1.01 0.002

2015 309,533 0.08 0.01 14.13 1.00 0.01 1.03 0.002

2016 319,311 0.08 0.01 14.14 0.99 0.00 0.98 0.002

2017 327,189 0.08 0.01 14.11 0.99 0.00 0.94 0.001

2018 329,567 0.09 0.01 14.59 0.99 0.00 0.94 0.001


The implementation of Pb emissions from Tyre and Break wear lead to an increase in Pb emissions over the entire time series.

NFR 1.A.3.c Railways

Table 209: Activities and Implied emission factors for heavy metals and POPs for 1.A.3.c Railsways 1990–2018.

Year Activity [TJ]

IEF Cd [kg/PJ]

IEF Hg [kg/PJ]

IEF Pb [kg/PJ]

IEF PAH [kg/PJ]

IEF Diox [g/PJ]

IEF HCB [g/PJ]

IEF PCB [g/PJ]

1990 2,380.2 0.18 0.32 2.6 8.7 0.02 3.3 0.0012

1991 2,182.9 0.18 0.32 2.6 8.7 0.02 3.3 0.0012

1992 2,165.2 0.18 0.33 2.7 8.8 0.02 3.4 0.0012

1993 2,110.6 0.17 0.31 2.5 8.6 0.02 3.2 0.0011

1994 2,129.4 0.17 0.30 2.5 8.6 0.02 3.2 0.0011

1995 1,986.9 0.19 0.34 2.8 8.8 0.02 3.4 0.0012

1996 1,796.4 0.20 0.37 3.0 9.1 0.02 3.6 0.0012

1997 1,787.8 0.12 0.21 1.7 7.9 0.01 2.5 0.0011

1998 1,761.1 0.11 0.19 1.6 7.8 0.01 2.4 0.0011

1999 1,818.3 0.11 0.18 1.5 7.7 0.01 2.3 0.0011

2000 1,814.5 0.10 0.16 1.3 7.5 0.01 2.2 0.0010

2001 1,746.2 0.08 0.12 0.9 7.2 0.01 1.9 0.0010

2002 1,889.4 0.08 0.12 1.0 7.2 0.01 1.9 0.0010

2003 1,895.6 0.06 0.10 0.8 7.1 0.01 1.7 0.0010

2004 1,885.8 0.04 0.04 0.3 6.7 0.01 1.3 0.0010

2005 2,194.0 0.03 0.03 0.2 6.6 0.01 1.3 0.0010

2006 2,143.2 0.03 0.04 0.3 6.6 0.01 1.6 0.0010

2007 2,131.0 0.03 0.03 0.3 6.6 0.01 1.6 0.0010

2008 2,127.4 0.03 0.03 0.2 6.5 0.01 1.6 0.0010

2009 2,084.6 0.04 0.04 0.3 6.6 0.01 1.7 0.0010

2010 2,039.3 0.03 0.03 0.2 6.5 0.01 1.7 0.0010

2011 1,714.8 0.03 0.04 0.3 6.5 0.01 1.7 0.0011

2012 1,764.6 0.03 0.04 0.3 6.5 0.01 1.7 0.0011

2013 1,626.0 0.04 0.04 0.3 6.6 0.01 1.7 0.0011

2014 1,700.1 0.03 0.04 0.3 6.5 0.01 1.8 0.0011



Year Activity [TJ]

IEF Cd [kg/PJ]

IEF Hg [kg/PJ]

IEF Pb [kg/PJ]

IEF PAH [kg/PJ]

IEF Diox [g/PJ]

IEF HCB [g/PJ]

IEF PCB [g/PJ]

2015 1,525.0 0.04 0.04 0.3 6.6 0.01 1.8 0.0010

2016 1,581.2 0.04 0.04 0.29 6.6 0.01 1.8 0.0010

2017 1,642.5 0.04 0.04 0.29 6.6 0.01 1.7 0.0010

2018 1,308.4 0.04 0.04 0.34 6.6 0.01 1.8 0.0009

NFR 1.A.3.d Navigation

Table 210: Activities and Implied emission factors for heavy metals and POPs for 1.A.3.d Navigation 1990–2018.

Year Activity [TJ]

IEF Cd [kg/PJ]

IEF Hg [kg/PJ]

IEF Pb [kg/PJ]

IEF PAH [kg/PJ]

IEF Diox [g/PJ]

IEF HCB [g/PJ]

IEF PCB [g/PJ]

1990 863 0.02 0.01 291.82 6.24 0.01 2.25 0.005

1991 780 0.02 0.01 264.90 6.23 0.01 2.37 0.005

1992 763 0.02 0.01 211.88 6.22 0.01 2.39 0.006

1993 769 0.02 0.01 151.98 6.23 0.01 2.38 0.006

1994 922 0.02 0.01 78.18 6.26 0.01 2.16 0.005

1995 1,016 0.02 0.01 0.03 6.27 0.01 2.06 0.004

1996 1,037 0.02 0.01 0.03 6.27 0.01 2.03 0.004

1997 1,029 0.02 0.01 0.03 6.27 0.01 2.04 0.004

1998 1,108 0.02 0.01 0.03 6.28 0.01 1.96 0.004

1999 1,085 0.02 0.01 0.03 6.28 0.01 1.98 0.004

2000 1,172 0.02 0.01 0.03 6.29 0.01 1.91 0.004

2001 1,218 0.02 0.01 0.03 6.29 0.01 1.87 0.003

2002 1,336 0.02 0.01 0.03 6.30 0.01 1.80 0.003

2003 1,095 0.02 0.01 0.03 6.28 0.01 1.95 0.004

2004 1,314 0.02 0.01 0.03 6.31 0.01 1.80 0.003

2005 1,290 0.02 0.01 0.03 6.30 0.01 1.80 0.003

2006 1,145 0.02 0.01 0.03 6.29 0.01 1.88 0.003

2007 1,216 0.02 0.01 0.03 6.30 0.01 1.83 0.003

2008 1,116 0.02 0.01 0.03 6.29 0.01 1.90 0.003

2009 966 0.02 0.01 0.03 6.27 0.01 2.02 0.003

2010 1,116 0.02 0.01 0.03 6.29 0.01 1.88 0.003

2011 1,009 0.02 0.01 0.03 6.28 0.01 1.95 0.003

2012 1,035 0.02 0.01 0.03 6.29 0.01 1.92 0.003

2013 1,098 0.02 0.01 0.03 6.30 0.01 1.86 0.002

2014 1,021 0.02 0.01 0.03 6.29 0.01 1.91 0.003

2015 867 0.02 0.01 0.03 6.27 0.01 2.05 0.003

2016 927 0.02 0.01 0.03 6.28 0.01 1.97 0.002

2017 949 0.02 0.01 0.03 6.29 0.01 1.94 0.002

2018 730 0.02 0.01 0.03 6.25 0.01 2.18 0.003



3.3 NFR 1.B Fugitive Emissions

Fugitive Emissions arise from the production and extraction of coal, oil and natural gas; their storage, processing and distribution. These emissions are fugitive emissions and are reported in NFR Category 1.B. Emissions from fuel combustion during these processes are reported in NFR Category 1.A.

3.3.1 Completeness

Table 211 gives an overview of the NFR categories included in this chapter and on the status of emission estimates of all sub categories. A “” indicates that emissions from this sub category have been estimated.



Table 211: Overview of sub categories of category 1.B Fugitive Emissions and status of estimation.

NFR Category Status

NEC gas CO PM Heavy metals

POPs

NO

x

SOx

NH

3

NM

VOC

CO

TSP

PM10

PM

2.5

Cd

Hg

Pb

PCD

D/F

PAH

HC

B

1.B.1.a Fugitive emissions from solid fuels: Coal mining and handling

1.B.1.a.i Coal Mining and Handling: Underground mines

050102Underground mining

NA NA NA NA NA NA NA NA NA NA

050103 Storage of solid fuels - Postmining activities


1.B.1.a.ii Coal Mining and Handling: Surface mines

050101Open cast mining NA NA NA NA NA NA NA NA NA NA

050103 Storage of solid fuels - Postmining activities


1.B.1.b Solid fuel transfor-mation(1)

IE IE IE IE IE IE IE IE IE IE IE IE IE IE

1.B.1.c Other - Other fugitive emissions from solid fuels (NFR - only Non-GHG)

050121 Peat production NO NO NO NO NO NO NO NO NO NO NO NO NO NO

1.B 2.a i Exploration, Production, Transport

0503 Extraction, 1st treatment and loading of gaseous fossil fuels

NA NA NA IE NA NA NA NA NA NA NA NA NA NA

iv Refining /Storage(2)

IE IE IE IE IE IE IE IE IE IE IE IE IE

v Distribution of oil products

050502 Transport and depots 050503 Service stations

NA NA NA NA NA NA NA NA NA NA NA NA NA

1.B.2.b Natural gas(3) 050301 Extraction - Land-based desulfuration

050302 Extraction - Land-based activities (other than desulfuration)

050601X51 Transmission fugitive and venting

050601X52 Storing

050603 Gas distribution networks

NA NA NA NA NA NA NA NA NA NA NA NA

1.B.2.c Venting and flaring(2)

IE IE IE IE IE IE IE IE IE IE IE IE IE IE

1.B.2.d Other fugitive emissions

NA NA NA NA NA NA NANE

NA NA NA NA NA

(1) included in 1.A.2.a Iron and Steel (2) included in 1.A.1.b Petroleum Refining (3) including emissions from 1.B.2.a.i (Exploration, Production and Transport of Oil) and oil pipelines



3.3.2 NFR 1.B.1.a Coal mining and handling – Methodological issues

In this category NMVOC, TSP, PM10 and PM2.5 emissions from coal mining and handling and TSP, PM10 and PM2.5 emissions from storage of solid fuels, including coke oven coke, bitumi-nous coal and anthracite, lignite and brown coal are considered.

NMVOC emissions were calculated based on activity data available in national statistics and re-ports (e.g. a report on mining (Montanhandbuch) by the Federal Ministry of Economy, Family and Youth (BMWFJ 2013)) and the tier 2 emission factor for open cast mining and underground mining given in the EMEP/EEA air pollutant emission inventory guidebook 2019. Before coal min-ing was stopped in 2007 (BMWFJ 2008) emissions decreased sharply (80%) between 2003 and 2004.

The emissions of TSP, PM10 and PM2.5 for Open Cast Mining were calculated by using the Tier 2 emission factors of the EMEP/EEA air pollutant emission inventory guidebook 2019. For the calculation of emissions from Underground Mining the Tier 1 emission factors were applied as there is no activity data available to apply the Tier 2 emission factors.

TSP, PM10 and PM2.5 emissions for the storage of solid fuels were calculated with the simple CORINAIR methodology. Activity data were taken from the national energy balance and are presented in Table 212 together with the national emission factors. The emission factors from the national study WINIWARTER et al. 2001 were converted by multiplying the emission factor with the respective net calorific value (Bituminous coal/Anthracite: 29.07 GJ/t, Lignite/Brown coal 10 GJ/t, Coke oven coke 29 GJ/t) to obtain emission factors in kg/kt.

Table 212: Emission factors fugitive TSP, PM10 and PM2.5 and NMVOC emissions from NFR category 1.B.1.a.

Storage of solid fuels Coal Mining and Handling PM Bituminous

coal/Anthracite Lignite/

Brown coal Coke oven

coke Open Cast

Mining Underground

Mining

EF [kg/kt] EF [g/t] EF [g/t]

TSP 96 85 108 82 89

PM10 45 40 51 39 42

PM2.5 14 12 16 6 5

NMVOC - - - 200 3000

Table 213: Activity data for fugitive TSP, PM10 and PM2.5 and NMVOC emissions from NFR category 1.B.1.a.

Year Activity [kt] Activity [kt]

Storage of solid fuels Mining activities

Bituminous coal Lignite Coke Oven

Coke Lignite Bituminous coal

1990 1 822 2 504 2 403 1 577 870

1995 1 484 1 743 2 354 1 271 27

2000 1 847 1 381 2 436 1 249 NO

2001 2 039 1 630 2 320 1 206 NO

2002 1 943 1 561 2 590 1 412 NO

2003 2 412 1 655 2 481 1 152 NO



Year Activity [kt] Activity [kt]

Storage of solid fuels Mining activities

2004 2 424 1 215 2 443 235 NO

2005 2 146 1 272 2 684 6 NO

2006 2 341 753 2 700 7 NO

2007 2 385 95 2 711 NO NO

2008 2 195 88 2 836 NO NO

2009 1 527 84 2 111 NO NO

2010 1 902 82 2 555 NO NO

2011 2 045 88 2 568 NO NO

2012 1 698 88 2 521 NO NO

2013 1 694 84 2 626 NO NO

2014 1 341 93 2 534 NO NO

2015 1 916 94 2 343 NO NO

2016 1 715 79 2 260 NO NO

2017 1 611 76 2 530 NO NO

2018 1 472 80 2 083 NO NO

3.3.3 NFR 1.B.2.a Oil – Methodological issues

As all oil fields are combined oil and gas production fields, total NMVOC emissions of combined oil and gas production are reported in this category. Further in this category, NMVOC emissions of transport and distribution of crude oil, oil products as well as from oil refining are considered.

Activity data for NMVOC emissions from natural gas extraction are reported from „Fachverband Mineralöl” (Austrian association of oil industry). NMVOC emissions are reported from 1992 on-wards, for the years before the emission value of 1992 was used.

Activity data for the transport of crude oil is reported by the Fachverband Mineralöl (Austrian as-sociation of oil industry). For the calculation of NMVOC emissions from this source an emission factor of 54 000 g/1 000m3 was used, taken from the 2006 IPCC Guidelines.

Emissions and activity data for refinery dispatch stations, transport and depots and from service stations and refuelling of cars (petrol) were reported directly from „Fachverband Mineralöl”. Activi-ty data for oil refining (crude oil refined) were taken from national statistics. An implied emission factor was calculated on the basis of emission and activity data. Activity data and implied emis-sion factors are presented in Table 214 .



Table 214: Activity data and implied emission factors for fugitive NMVOC emissions from NFR category 1.B.2.a.

Year Transport of crude oil112

Refinery dispatch station Oil refining

Activity [1 000m3]

IEF [g/t] NMVOC Gasoline [kt] IEF [g/t] NMVOC Crude oil refined [kt]

1990 7 993 1 109 2 554 472 7 952

1995 8 721 916 2 402 174 8 619

2000 8 720 811 1 980 168 8 240

2001 8 855 296 1 998 62 8 799

2002 9 020 281 2 142 62 8 947

2003 9 309 269 2 223 62 8 819

2004 8 930 262 2 133 59 8 442

2005 9 000 205 2 073 59 8 743

2006 8 810 221 1 992 60 8 472

2007 9 090 228 1 966 60 8 496

2008 9 380 183 1 835 58 8 710

2009 8 930 186 1 842 57 8 286

2010 8 300 171 1 821 55 7 719

2011 8 900 181 1 756 50 8 170

2012 9 200 173 1 715 47 8 349

2013 9 300 169 1 665 40 8 584

2014 9 300 183 1 624 48 8 435

2015 9 500 161 1 640 44 8 853

2016 8 900 139 1 638 50 8 184

2017 9 000 157 1 619 58 8 064

2018 9 800 128 1 658 42 8 970

Year Transport and depots Service stations

IEF [g/t] NMVOC Gasoline [kt] IEF [g/t] NMVOC Petrol [kt]

1990 995 2 554 736 2 554

1995 986 2 402 662 2 402

2000 241 1 980 270 1 980

2001 238 1 998 269 1 998

2002 264 2 142 270 2 142

2003 233 2 223 270 2 223

2004 215 2 133 270 2 133

2005 206 2 073 270 2 073

2006 233 1 992 270 1 992

2007 233 1 966 270 1 966

2008 246 1 835 270 1 835

2009 151 1 842 270 1 842 112 Refinery crude oil throughput



Year Transport and depots Service stations

IEF [g/t] NMVOC Gasoline [kt] IEF [g/t] NMVOC Petrol [kt]

2010 119 1 972 270 1 821

2011 112 1 886 270 1 756

2012 134 1 853 270 1 715

2013 134 1 798 270 1 665

2014 151 1 730 270 1 624

2015 143 1 725 270 1 640

2016 146 1 723 270 1 638

2017 125 1 744 270 1 619

2018 127 1 794 270 1 658

Between 1990 and 2018 NMVOC emissions from the transport of crude oil increased by 23% due to the increased refinery activity.

NMVOC emissions from refinery dispatch stations, transport and depots and from service stations and refuelling of cars decreased remarkably (93%, 91% and 76% respectively) between 1990 and 2018 due to installation of gas recovery units.

NMVOC emissions from oil refining and gas extraction also showed a notable decrease of 90% and 66% respectively between 1990 and 2018. This emission reduction has been achieved through technical improvements (e.g. improved tanks and loading units).

3.3.4 NFR 1.B.2.b Natural Gas – Methodological issues

In this category SO2 emissions from the first treatment of sour gas and NMVOC emissions from gas extraction and gas distribution networks are considered.

SO2 emissions and activity data for the first treatment of sour gas are reported from „Fachverband Mineralöl” (Austrian association of oil industry). The drop in SO2 emissions after 1996 is due to the implementation of pollution control measures. Emission data for 1990‒1998 as well as for 2013‒2018 were taken from the „Fachverband Mineralöl”, for the years in between (1999‒2012) an EF of 120 g/1 000m3 was used, based on an expert opinion on the sulphur emission level of desulfurization in Austria’s refinery plant. The drop of -36% of raw gas throughput in 2016 was due to the failure of one sour gas tube in one plant.

Activity data and NMVOC emissions from gas extraction are reported by the „Fachverband Min-eralöl” (Austrian association of oil industry). NMVOC emissions from gas distribution networks were calculated by applying the country-specific share of 1.2% NMVOC in natural gas. This share is based on the natural gas composition in Austria. Emissions were directly linked to CH4 emissions that were calculated applying a tier 2 method based on the material specific distribu-tion pipeline lengths (reported by “Fachverband der Gas- und Wärmeversorgungsunter-nehmungen”, “Association of Gas- and District Heating Supply Companies”) and material specif-ic emission factors (WARTHA 2005).



Table 215: Activity data and implied emission factors for fugitive NMVOC and SO2 emissions from NFR category 1.B.2.b.

Year First treatment desulfura-tion

Gas extraction Gas distribution

IEF [g/1 000 m3]

SO2

Raw gas Throughput [1 000 m3]

IEF [g/1000m3] NMVOC

Gas produc-tion

[1000m3]

IEF [g/km] NMVOC

Distribution mains [km]

1990 8 061.59 248 090 849 1 288 000 2 043 11 672

1995 3 771.84 405 638 676 1 482 000 1 248 17 778

2000 120.00 358 357 525 1 805 000 864 24 099

2001 120.00 393 492 485 1 954 000 829 25 042

2002 120.00 347 513 468 2 014 000 833 24 216

2003 120.00 408 198 465 2 030 000 797 25 699

2004 120.00 373 099 472 1 963 000 744 26 158

2005 120.00 338 349 557 1 637 000 724 26 958

2006 120.00 402 990 501 1 819 000 713 27 413

2007 120.00 444 029 284 1 848 000 696 27 945

2008 120.00 372 406 289 1 531 000 682 28 348

2009 120.00 466 628 300 1 670 000 673 28 533

2010 120.00 397 132 288 1 816 000 662 28 733

2011 120.00 375 168 295 1 684 000 659 29 023

2012 120.00 375 420 270 1 807 000 650 29 260

2013 116.11 335 874 319 1 467 000 634 29 469

2014 117.08 307 475 397 1 247 000 625 29 826

2015 139.73 279 102 383 1 166 000 617 30 067

2016 128.15 179 474 352 1 253 000 608 30 215

2017 142.38 252 837 235 1 742 000 597 30 507

2018 96.79 237 622 379 969 000 597 30 089

3.3.5 NFR 1.B.2.d Other fugitive emissions from energy production – Methodological issues

In this category, NH3- and Hg-emissions from energy production from geothermal energy are considered.

NH3- and Hg-emissions were calculated based on activity data available in the national energy balance (Table 216) and the Tier 1 emission factors for other fugitive emissions from energy productions in Table 3-1 of the EMEP/EEA air pollutant emission inventory guidebook 2019 (2100 g NH3/MWh electricity produced and 0.44g Hg/MWh electricity produced).

Table 216: Activity data for fugitive NH3- and Hg- emissions from NFR category 1.B.2.d

year geothermal energy extraction [GWh]

1990 NO

1995 NO

2000 NO



2001 NO

2002 NO

2003 NO

2004 NO

2005 2.30

2006 3.06

2007 2.41

2008 1.62

2009 1.51

2010 1.40

2011 1.05

2012 0.68

2013 0.31

2014 0.38

2015 0.06

2016 0.02

2017 0.09

2018 0.24

3.3.6 Category-specific QA/QC

Activity Data received from the Austrian Association of oil industry (Fachverband der Miner-alölindustrie) is compared with Energy Balance data on a regular basis. If differences occur the-se are clarified with external experts and are well explained and documented.

3.3.7 Uncertainty Assessment

Table 217 gives an overview of uncertainties for fugitive emissions, estimated according to the EMEP/EEA Emission Inventory Guidebook 2019 (EEA 2019). An average of the default values, based on the definitions of the qualitative ratings given in (EEA 2019) is used (see also chapter 1.7, Table 25).

Table 217: Uncertainties for activity data, emission factors and combined uncertainties for SO2, NMVOC and PM2.5 for fugitive emissions.

Sector Pollutant Uncertainty AD Uncertainty EF Combined uncertainties

1.B.2.b SO2 5.0% 20.0% 20.62%

1.B.1.a NMVOC 5.0% 20.0% 20.62%

1.B.2.a NMVOC 0.5% 20.0% 20.01%

1.B.2.b NMVOC 5.0% 20.0% 20.62%

1.B.1.a PM2.5 5.0% 200.0% 200.06%



3.3.8 Category-specific Recalculations

Recalculations of TSP, PM10 and PM2.5 emissions in the category 1.B.1.a (Coal Mining and Handling) for the years 2005–2017 are due to a revision of the energy balance by Statistik Aus-tria. This revision leads to an increase of 0.003 kt TSP emissions, 0.001 kt PM10 emissions and 0.0004 kt PM2.5 emissions in 2017 Recalculations of NH3- and Hg-emissions for the years 2005–2017 are due to the new estima-tion of fugitive emissions from energy production in geothermal energy (subcategory 1.B.2.d) and lead to an increase of 0.0005kt NH3 and 0.0001kt Hg in 2017.

3.3.9 Planned Improvements

No improvements are currently planned.

Austria’s Informative Inventory Report (IIR) 2020 – Industrial Processes and Product Use (NFR Sector 2)


4 INDUSTRIAL PROCESSES AND PRODUCT USE (NFR SECTOR 2)

4.1 Sector overview

This chapter includes information on the estimation of emissions of NEC gases, CO, particulate matter (PM), heavy metals (HM) and persistent organic pollutants (POPs) as well as references for activity data and emission factors reported under NFR Category 2 Industrial Processes and Product Use for the period from 1990 to 2018.

Emissions from this sector arise from the following categories: Mineral Products (2.A) Chemical Industry (2.B) Metal Production (2.C) Solvent use (2.D.3) Other product use (2.G) Other production (2.H) Wood processing (2.I) Only process related emissions are considered in this sector; emissions due to fuel combustion in manufacturing industries are allocated to NFR Category 1.A.2 Fuel Combustion – Manufac-turing Industries and Construction (see Chapter 3.1.4).

4.1 General description

4.1.1 Completeness

Table 218 gives an overview of the NFR categories included in this chapter. A “” indicates that emissions from this sub category have been estimated, “NA” indicates that the pollutant in ques-tion is not emitted during the respective industrial process.

Some categories in this sector are not occurring (NO) in Austria as there is no such produc-tion/use. For some categories, emissions are included elsewhere (IE). In Chapter 1.8, a general description regarding completeness is given.



Table 218: Completeness of sub categories in sector 2 Industrial Processes and Product Use.

NFR Category Status


POPs

NO

x

SO2

NH

3

NM

VOC

CO

TSP

PM10

PM2.

5

Cd

Hg

Pb

Dio

xin

PAH

HC

B

PCB

2.A.1 Cement Production(7) IE IE IE IE IE IE IE IE IE IE IE IE

2.A.2 Lime Production NA NA NA NA NA NA NA NA NA NA NA NA

2.A.3 Glass production IE IE IE IE IE IE IE IE IE IE IE IE IE IE IE

2.A.5 Mining, construction/demolition and handling of products(5)


2.A.6 Other Mineral products NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO

2.B.1 Ammonia Production IE IE(1) NA NA NA NA NA NA NA NA NA NA

2.B.2 Nitric Acid Production NA NA NA NA NA NA NA NA NA NA NA NA NA

2.B.3 Adipic Acid Production NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO

2.B.5 Carbide Production NA NA NA NA NA NE NE NE NA NA NA NA NA NA NA

2.B.6 Titanium Dioxide Production NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO

2.B.7 Soda Ash Production NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO

2.B.10 Chemical Industry: Other(4) NA NE(2) NA NA(3)

2.C.1 Iron and steel production IE

2.C.2 Ferroalloys production NA NA NA NA NA NE NE NE NE NE NE NA

2.C.3 Aluminium production NA NA NA NA NA NA NA NE NA

2.C.4 Magnesium production NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO

2.C.5 Lead production(6) NA IE NA NA NA NE NA NA

2.C.6 Zinc production NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO

2.C.7.a Copper production NA NA NE NE NE

2.C.7.b Nickel production NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO

2.C.7.c Other metal production NA NE NE NE NE NE NE NE NE NE NA

2.C.7.d Storage, handling and transport of metal products

NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO

2.D.3.a Domestic solvent use (incl. fungicides) NA NA NA NA NA NA NA NA NA NA NA NA NA

2.D.3.b Road paving with asphalt NA NA NA NA NA NA NA NA NA NA NA NA NA NA

2.D.3.c Asphalt roofing NA NA NA NE NA NA NA NA NA NA NA NA NA NA

2.D.3.d Coating application NA NA NA NA NA NA NA NA NA NA NA NA NA NA

2.D.3.e Degreasing NA NA NA NA NA NA NA NA NA NA NA NA NA NA

2.D.3.f Dry Cleaning NA NA NA NA NA NA NA NA NA NA NA NA NA NA



NFR Category Status


POPs

NO

x

SO2

NH

3

NM

VOC

CO

TSP

PM10

PM2.

5

Cd

Hg

Pb

Dio

xin

PAH

HC

B

PCB

2.D.3.g Chemical Products NA NA NA NA NA NA NA NA NA NA NA NA

2.D.3.h Printing NA NA NA NA NA NA NA NA NA NA NA NA NA NA

2.D.3.i Other solvent use NA NA NA NA NA NA NA NA NA NA NA NA NA NA

2.G Other product use NE NA

2.H OTHER PROCESSES NA NA NA NA NA NA NA NA

2.I WOOD PROCESSING NA NA NA NA NA NA NA NA NA NA NA NA

2.J PRODUCTION OF POPs NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO

2.K CONSUMPTION OF POPs AND HEAVY METALS

NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO

2.L OTHER NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO (1) included in 2.B.10 Other (2) PAH emissions from graphite production (production of graphite electrodes only) are not estimated, as no emission

factor is available. (3) until 1992 from Tri-, Perchlorethylene Production; later NO (4)2.B.10.b is included in 2.B.10.a (5)2.A.5.c is included in 2.A.5.a (6) included in 1.A.2.b (7) included in 1.A.2.f


The key category analysis is presented in Chapter 1.5. This chapter includes information on the IPPU sector. Key sources within this category are presented in Table 219.

Table 219: Key sources of sector IPPU.

NFR Category

Source Categories Key Categories

Pollutant KS-Assessment

2.A.5 Mining, construction/demolition and han-dling of products

TSP, PM10, PM2.5 LA, TA

2.C.1 Iron and Steel Production Cd, Pb, Hg, DIOX, PCB, HCB T PM10,

LA, TA

2.C.3 Aluminium production DIOX, LA,TA

2.D.3.a Domestic solvent use including fungicides NMVOC LA,TA

2.D.3.d Coating applications NMVOC LA,TA

2.D.3.h Printing NMVOC LA, TA

2.G Other product manufacture and use Cd LA, TA



NFR Category

Source Categories Key Categories

Pollutant KS-Assessment

2.H Other Processes NMVOC LA, TA

2 I Wood Processing TSP LA, TA TA = Trend Assessment 2018 LA = Level Assessment (if not further specified – for the years 1990 and 2018) 4.1.3 Methodology

The general method for estimating emissions for the industrial processes and product use sec-tor is multiplying production data for each process by an emission factor per unit of production (CORINAIR simple methodology).

In some categories, emission and production data were reported directly by industry or by asso-ciations of industries and thus represent plant-specific data.

Information on which NFR categories of IPPU sector include the condensable component of PM10 and PM2.5 can be found in chapter 12.3.


The table below gives an overview of uncertainties for Industrial Processes and Product Use for selected pollutants. The method used for the assessment of uncertainty is according to the EMEP/EEA air pollutant emission inventory guidebook 2016 (EEA 2016). Further information on the uncertainty assessment of activity data can be found in Austria`s National Inventory Report (UMWELTBUNDESAMT 2020a). Where no specific information on uncertainties of emission factors was available, an average of the default values, based on the definitions of the qualitative rat-ings given in the EMEP/EEA Emission Inventory Guidebook 2016 is used. For more details on uncertainties please refer to 1.7 .

Table 220: Uncertainties for activity data, emission factor and combined uncertainties for NOx, SO2, NMVOC, NH3 and PM2.5 for Industrial Processes and Product Use

NRF sector Pollutant Activity data uncertainty (%)

Emission factor uncertainty (%)

Combined uncertainty (%)

2.A.1 PM2.5 1.1 40.0 40.0

2.A.2 PM2.5 1.6 125.0 125.0

2.A.5 PM2.5 5.0 200.0 200.1

2.B.1 NOx 2.0 40.0 40.0

2.B.1 NH3 2.0 20.0 20.1

2.B.2 NOx 2.0 40.0 40.0

2.B.2 NH3 2.0 20.0 20.1

2.B-10 SO2 2.0 40.0 40.0

2.B-10 NOx 2.0 40.0 40.0

2.B-10 NMVOC 2.0 20.0 20.1

2.B-10 PM2.5 2.0 20.0 20.1

2.B-10 NH3 2.0 20.0 20.1



NRF sector Pollutant Activity data uncertainty (%)

Emission factor uncertainty (%)

Combined uncertainty (%)

2.C.1 SO2 0.5 125.0 125.0

2.C.1 NOx 0.5 40.0 40.0

2.C.1 NMVOC 0.5 125.0 125.0

2.C.1 PM2.5 0.5 20.0 20.0

2.C.2 PM2.5 5.0 40.0 40.3

2.C.3 PM2.5 2.0 40.0 40.0

2.C.5 PM2.5 10.0 40.0 41.2

2.C.7 SO2 5.0 125.0 125.1

2.C.7 NOx 5.0 40.0 40.3

2.C.7 NMVOC 5.0 125.0 125.1

2.C.7 PM2.5 5.0 40.0 40.3

2.D NMVOC 5.0 30.0 30.4

2.G SO2 20.0 125.0 126.6

2.G NOx 20.0 125.0 126.6

2.G NMVOC 20.0 125.0 126.6

2.G PM2.5 20.0 125.0 126.6

2.G NH3 20.0 40.0 44.7

2.H NOx 10.0 40.0 41.2

2.H NMVOC 10.0 40.0 41.2

2.H PM2.5 10.0 200.0 200.2

2.I PM2.5 1.0 40.0 40.0


For the Austrian inventory, a quality management system is in place. For further information see Chapter 1.6. Concerning measurement and documentation of emission data there are also spe-cific regulations in the Austrian legislation as presented in Table 221, which also address verifica-tion. Some plants that report emission data have quality management systems according to the ISO 9000 series or similar systems in place.



Table 221: Austrian legislation with specific regulations concerning measurement and documentation of emission data.

Source Category

Austrian legislation

2.A.1 BGBl. II Nr. 60/2007 Zementverordnung 2007

2.A.7 BGBI 1994/498 Verordnung für Anlagen zur Glaserzeugung

2.C.1 BGBl. II Nr. 264/2014 Gießerei-Verordnung 2014

2.C.1 BGBI II 1997/160 Verordnung für Anlagen zur Erzeugung von Eisen und Stahl

BGBl. II 2007/290 Änderung der Verordnung über die Begrenzung der Emission von luftverunreinigenden Stoffen aus Anlagen zur Erzeugung von Eisen und Stahl

2.C.1 BGBl. II Nr. 160/1997 Begrenzung der Emission von luftverunreinigenden Stoffen

2.C.1 BGBl. III Nr. 141/2004 Protokoll zu dem Übereinkommen von 1979 über weiträumige grenzüberschreitende Luftverunreinigung betreffend Schwermetalle samt Anhängen und Erklärungen (in Anhang 2 angeführt)

2.D.3 BGBl. I Nr. 111/2002 VOC-Anlagen-Verordnung

2.A/2.B/2.C/2.D BGBI II 1997/331 Feuerungsanlagen-Verordnung

2.C 2/2.C 3/2.C 5 BGBl. II Nr. 86/2008 Begrenzung der Emission von luftverunreinigenden Stoffen aus Anlagen zur Erzeugung von Nichteisenmetallen und Refraktärmetallen – NER-V

2.A/2.B/2.C/2.D BGBL I 115/1997 Immissionsschutzgesetz – Luft, IG-L

2.A/2.B/2.C/2.D BGBl I 127/2013 Emissionsschutzgesetz für Kesselanlagen – EG-K 2013


2.A.5.b Construction and demolition The methodology to calculate the particulate matter emissions from construction and demolition based on the EMEP/EEA Guidebook 2019 will be compared to the country-specific methodolo-gy in future submissions.

2.D.3.cAsphalt roofing This subsector has been updated during the evaluation of the solvents model: all of the Austrian production sites have installed off-gas treatment systems and in the past years, emissions have been negligible. Therefore the notation key has been changed to NE. The time series will be re-vised, when data on the insertion of the abatement technologies are fully investigated. The in-vestigation is planned for the next submission.

2.D.3.bRoad paving with asphalt PM2.5 will be estimated, when data on plants and abatement technologies in place are fully in-vestigated. The investigation is planned for the next submission.



4.2 NFR 2.A.1-2.A.3 Mineral Products

4.2.1 Fugitive Particulate Matter emissions

4.2.1.1 Source Category Description

In this category, fugitive PM emissions from bulk material handling are reported. These include emissions from quarrying and mining of minerals other than coal, construction and demolition and agricultural bulk materials. Most fugitive PM emissions are reported in NFR category 2.A.5, except emissions from cement that are reported in NFR category 2.A.1, from lime production that are reported in NFR category 2.A.2, and from agricultural bulk material that are reported in NFR category 3.D. Emissions from cement and lime production include point source emissions from kilns.

4.2.1.2 Methodological Issues

The general method for estimating fugitive particulate matter emissions is multiplying the amount of bulk material by an emission factor (CORINAIR simple methodology). All emission factors were taken from a national study (WINIWARTER et al. 2001) that has been partly updated or amended (WINIWARTER et al. 2007): new emission factors for handling bulk materials and updated methodology according to

VDI113 guidelines 3790; the inclusion of PM emissions from cement and limestone kilns from 1.A.2.f Other Industry

under 2.A.1 and 2.A.2; updated methodology and emission factors for construction and demolition based on the

CEPMEIP project114.

In 2011, a confidential study was commissioned by the Association for Building Materials and Ceramic Industries, which contains a new EF for PM10 for limestone (AMANN & DÄMON, 2011). The calculation was based on the evaluation of 20 studies, comparing different quarries, also for dolomite and basaltic rocks. It showed that the EF can be used for all three types of material. For the calculation of emission factors for PM2.5 and TSP, the relation TSP 100%, PM10 46.51%, PM2.5 4.65% was used (WINIWARTER et al. 2007). For data before 2000, EFs were calculated us-ing the same ratio, but a higher EF for dolomite, based on the study by WINIWARTER et al. (2001). Changes in emission factors over time can be explained by changes in material handling and dust abatement technology.

Emission factors are presented in Table 222. Activity data are mainly taken from national statis-tics and presented in Table 223.

113 Association of German Engineers – VDI Verein Deutscher Ingenieure 114 http://www.air.sk/tno/cepmeip/



Table 222: Emission factors (EF) for diffuse PM emissions from bulk material handling, mining and construction/demolition

Bulk material / mineral EF TSP [g/t] EF PM10 [g/t] EF PM2.5 [g/t]

Magnesite (1) 216.20 101.61 10.81

Sand (1) 525.00 246.75 26.25

Gravel (1) 135.00 63.45 6.75

Silicates (1) 191.00 89.77 9.55

Dolomite (4) (3) 141.90 (184.45) 66.00 (85.80) 6.60 (8.58)

Limestone (3) 141.90 66.00 6.60

Basaltic rocks (3) 141.90 66.00 6.60

Iron ore 216.78 104.70 30.43

Tungsten ore 25.12 11.86 3.75

Gypsum, Anhydride (1) 85.60 40.23 4.28

Lime (1) 122.70 110.43 79.76

Cement (2) (1) 11.4 (21.8)(41.9) 10.3 (19.6)(37.7) 9.2 (17.4)(33.5)

Cement & Lime milling 7.75 6.98 6.20

Rye flour 43.59 20.62 6.50

Wheat flour 43.59 20.62 6.50

Sunflower and rapeseed grist 24.76 11.85 3.79

Wheat bran and grist 10.90 5.16 1.63

Rye bran and grist 10.90 5.16 1.63

Concentrated feedingstuffs 30.28 14.32 4.51

Activity EF TSP [g/m2] EF PM10 [g/m2] EF PM2.5 [g/m2]

Total area under construction (for sub-category „Construction and demolition“ (1)

173.4 86.7 8.67

(1) Source: WINIWARTER et al. 2007 (2) Decreasing EF values are given for 2012 (2006)(1990) (3) Source: Amann & Dämon 2011 (4) Decreasing EF values are given for 2012 (1990)

Table 223: Activity data for diffuse PM emissions from bulk material handling, mining and construction/demolition

Activity data [t] 1990 1995 2000 2005 2010 2015 2018

Magnesite 1 179 162 783 497 725 832 693 754 757 063 702 504 808 239

Sand 2 517 296 3 033 907 3 692 910 3 660 228 2 001 407 2 169 684 2 278 274

Gravel 14 264 676 17 192 140 20 978 974 25 361 797 28 304 033 27 550 482 26 800 600

Silicates 1 484 527 810 520 1 991 018 2 580 295 2 593 863 2 017 977 2 155 109

Dolomite 1 879 837 8 789 688 7 152 245 6 291 413 3 914 859 3 963 986 4 346 730

Limestone 15 371 451 19 079 581 23 823 529 22 643 754 21 189 887 21 059 817 21 076 927

Basaltic rocks 3 673 535 4 202 244 4 933 202 3 166 281 3 234 408 3 543 675 3 513 876



Activity data [t] 1990 1995 2000 2005 2010 2015 2018

Iron ore 2 310 710 2 116 099 1 859 449 2 047 950 2 068 853 2 783 327 2 803 536

Tungsten ore 191 306 411 417 416 456 472 964 429 748 535 762 544 390

Gypsum, An-hydride

751 645 958 430 946 044 911 162 872 273 715 195 836 862

Lime, quick, slacked

512 610 522 934 654 437 788 328 764 845 772 225 734 579

Cement 3 693 539 2 929 973 3 052 974 3 221 167 3 097 043 3 256 561 3 551 969

Cement & Lime milling

2 450000 2 450 000 2 450 000 2 450 000 2 450 000 2 450 000 2 450 000

Rye flour 61 427 55 846 48 054 62 387 84 997 86 926 58 133

Wheat flour 259 123 287 461 291 482 324 160 451 086 516 638 381 911

Sunflower and rapeseed grist

19 900 108 600 121 200 121 200 121 200 121 200 121 200

Wheat bran and grist

64 781 71 865 73 303 100 185 126 075 134 681 124 971

Rye bran and grist

15 357 13 962 13 139 13 139 13 139 13 139 13 139

Concentrated feeding stuff

638 014 720 972 980 808 1 018 649 988 371 1 113 408 1 145 577

Activity data [m2]

1990 1995 2000 2005 2010 2015 2018

Total area under construction (for sub-category „Construction and demolition“

10 142 004 11 060 799 11 788 151 11 941 513 13 504 469 13 804 436 15 275 921

4.2.2 NFR 2.A.5 Mining, Construction/Demolition


This category contains the sub categories “quarrying and mining of minerals other than coal” and “construction and demolition”. It covers, inter alia, particulate matter emissions from gypsum and anhydrite mining and from construction/demolition activities.


Mining activities for the years 1990, 1995 and 1999 were taken from WINIWARTER et al. (2001). From 2000 onwards, annual data from the Austrian mining handbook (e.g. BMWFW 2018) were used. Particulate matter emission factors for gypsum and anhydrite mining were taken from WINIWARTER et al. (2007).

Construction and demolition emissions are based on data from Statistik Austria on the total area under construction (in m²). This area is multiplied by emission factors for TSP, PM10 and PM2.5 derived by WINIWARTER et al. (2007).

Emission factors and activity data for mining, construction/demolition and handling of products are presented in Table 222 and Table 223, above.


No recalculations have been made for this year’s submission.



4.3 NFR 2.B Chemical Products

4.3.1 NFR 2.B.1 Ammonia and 2.B.2 Nitric Acid Production


Ammonia (NH3) is produced by catalytic steam reforming of natural gas or other light hydrocar-bons (e.g. liquefied petroleum gas, naphtha). Nitric acid (HNO3) is produced from ammonia (NH3), where in a first step NH3 reacts with air to NO and NO2 and then reacts with water to form HNO3. Both processes are minor sources of NH3 and NOx emissions. During ammonia produc-tion, small amounts of CO are emitted.

In Austria there is only one producer of ammonia and nitric acid.

The following chart (Figure 44) depicts the process of ammonia synthesis, the main production lines (ammonia, urea, melamine, nitric acid, fertiliser etc.) with their main raw material as well their internal subsequent processing of related products (UMWELTBUNDESAMT 2004c). A detailed process description of the Ammonia production and downstream processes can be found in the Austria`s National Inventory Report (UMWELTBUNDESAMT 2020a).



Scheme of ammonia synthesis and related production processes

Proc

esse

s en

tirel

y fo

cuss

ed o

n fe

rtili

zer p

rodu

ctio

n

NH3

NOx

NOx

NH3

NOx

Natural gas Air

CO2 CO2

CO2 NH3

Ammonia

Nitric Acid

Air

Urea

ODDA plant

Rock Phosphate

Conversion of Calcium Nitrate

Ammonium nitrate

AN

NH3

NH3

Urea

NP,NPK- fertiliser

Granulation NPK

Granulation CAN

CAN- fertiliser

AN

Production of technical grade AN

CO2

Water

Melamine*)

Calcium Nitrate

HNO3

HNO3

Lime *) waste gases from prod-

uction of melamine are used for the production of urea and for prod-uction of fertilisers

Urea-AN solution

Ammoni- ation

NH3

NP acid

AN

CO2

NH3

NOx

NH3

NH3

Figure 44: Scheme of ammonia synthesis and related production processes.


Activity data from 1990 onwards and emission data from 1994 onwards were reported directly to UMWELTBUNDESAMT by the only producer in Austria and thus represent plant specific data. From emission and activity data, an implied emission factor (IEF) was calculated (see Table 224 and Table 225). The calculated implied emission factor (IEF) for 1994 was applied to calculate emissions for the years 1990 to 1993, as no emission data were available for these years.

The IEF for NOx from ammonia production fluctuate somewhat due to process intrinsic fluctua-tions. The lower vales result from a change of combustion temperature in the plant. NOx emis-sions from 1990 to 1992 are included in category 2.B.5 Other processes in organic chemical in-dustries.




NH3 emission factors vary depending on plant utilization, catalyst activity as well as on the fre-quency of production process interruptions (start-ups result in higher emissions), e.g. because of technical problems or catalyst change.

Table 224: Emissions and implied emission factors for NOx, NH3 and CO from ammonia production (NFR Category 2.B.1).

Year NOx emission [t]

NOx IEF [g/t]

NH3 emission [t]

NH3 IEF [g/t]

CO emission [t]

CO IEF [g/t]

1990 IE NA 7.4 16.0 123.1 267.1

1995 285.9 604.4 10.7 22.6 95.1 201.1

2000 206.5 428.1 7.0 14.5 43.0 89.2

2005 244.0 509.9 9.9 20.7 52.6 109.9

2010 197.7 399.1 10.7 21.6 56.9 114.9

2015 198.4 381.6 9.5 18.3 61.2 117.7

2018 171.2 422.6 12.4 30.6 64.8 160.0

Table 225: Emissions and implied emission factors for NOx and NH3 from nitric acid production (NFR Category 2.B.2).

Year NOx emission [t] NOx IEF [g/t] NH3 emission [t] NH3 IEF [g/t]

1990 IE NA 1.4 2.6

1995 346.3 715.5 0.1 0.2

2000 406.5 761.6 0.4 0.7

2005 239.2 428.8 0.1 0.1

2010 144.0 262.9 7.8 14.2

2015 74.9 133.2 4.3 7.6

2018 51.1 118.9 4.6 10.7

4.3.2 NFR 2.B.10 Other Chemical Industry


This category includes NH3 emissions from the production of ammonium nitrate, fertilizers and urea as well as NOx emissions from fertilizer production. For the years 1990 to 1992, all NOx emissions from inorganic chemical processes are reported as a total under this category.

This category furthermore includes SO2 and CO emissions from inorganic chemical processes and NMVOC emissions from organic chemical processes, which were not further split into sub categories.

Emissions of minor importance are Heavy metals and particulate matter from fertilizers; PAH emissions from graphite production;



Hg emissions from chlorine production (1999 changeover from mercury cell to membrane cell, thus no more emissions);

HCB emissions from the production of per- and trichloroethylene (1992 cessation of produc-tion) and

Particulate matter emissions from the production of ammonium nitrate. NMVOC emissions on facility level from chemical production; the emissions from smaller

plants are included in the solvents model Emissions from storage, handling and transport of chemical products are included in NFR

2.B.10.a 4.3.2.2 Methodological Issues

Ammonium nitrate and urea production

For ammonium nitrate and urea production, activity data from 1990 onwards and emission data from 1994 onwards were reported directly to UMWELTBUNDESAMT by the only producer in Austria and thus represent plant specific data.

NH3 emissions were reported separately for each of the two production processes; CO emis-sions occur during urea production only. The implied emission factors for NH3 and CO that were calculated from activity and emission data of 1994 were applied to calculate emissions of the years 1990 to 1993 as no emission data were available for these years.

TSP emissions from ammonium nitrate production were also reported directly to UMWELT-BUNDESAMT by the only producer in Austria and represent plant specific data. The shares of PM10 and PM2.5 are 90% and 80%, respectively, until 1996 (conventional plant) and 95% and 90% from 1997 onwards (modern plant), according to UMWELTBUNDESAMT (2001c).

Table 226: NH3, TSP, PM10 and PM2.5 emissions and implied emission factors for NH3 emissions from Ammonium nitrate production.

Year NH3 emission [t]

NH3 IEF [g/t] TSP emission [t]

PM10 emission [t]

PM2.5 emission [t]

1990 0,71 72,39 12,80 11,52 10,24

1995 0,90 72,39 14,90 13,41 11,92

2000 0,20 12,89 0,20 0,19 0,18

2005 0,33 17,20 0,26 0,24 0,23

2010 0,30 23,08 0,20 0,19 0,18

2015 0,30 23,10 0,10 0,10 0,09

2018 0,40 31,69 0,10 0,10 0,09

Table 227: Emissions and implied emission factors for NH3 and CO emissions from urea production.

Year NH3 emission [t] NH3 IEF [g/t] CO emission [t] CO IEF [g/t]

1990 38.6 137.0 7.1 7.1

1995 47.7 121.4 9.7 9.7

2000 17.4 44.6 3.6 3.6

2005 30.1 72.3 3.8 3.8



Year NH3 emission [t] NH3 IEF [g/t] CO emission [t] CO IEF [g/t]

2010 33.8 80.5 3.7 3.7

2015 42.8 98.5 3.7 3.7

2018 36.8 104.6 3.3 3.3

Fertilizer production

For fertilizer production activity, data from 1990 to 1994 were taken from national production statistics115 (Statistik Austria); NOx and NH3 emissions and activity data from 1995 onwards were reported by the main producer in Austria. For the years 1990 to 1993, NH3 emissions were estimated using information on emissions from the main producer and extrapolation to total pro-duction. The emission estimate for 1994 was obtained by applying the average emission factor of the years 1995 to 1999. NOx emissions from 1990 to 1992 are included in Other processes in organic chemical industries.

Cd, Hg and Pb emissions were calculated by multiplying the above mentioned activity data by national emission factors (HÜBNER 2001a) that derive from analysis of particulate matter frac-tions as described in MAGISTRAT DER LANDESHAUPTSTADT LINZ (1995). Particulate matter emis-sions (fugitive and non-fugitive) were estimated for the whole fertilizer production in Austria (WINIWARTER et al. 2007) for the years 1990, 1995 and 1999. Implied emission factors were cal-culated from emission and activity data that were used to calculate emissions from 2000 to 2005. The shares of PM10 and PM2.5 are 58.6% and 30.9%, respectively, for the whole time-series.

Table 228: NOx and NH3 emissions from fertilizer production.

Year NOx emission [t] NOx IEF [g/t] NH3 emission [t] NH3 IEF [g/t]

1990 IE IE 218.7 157.5

1995 60.0 65.5 37.2 40.6

2000 71.4 69.8 73.2 71.6

2005 89.4 85.6 25.4 24.3

2010 81.4 77.4 36.0 34.3

2015 115.9 111.0 22.8 21.8

2018 53.9 67.6 24.7 31.0

Table 229: Heavy metal and particulate matter emissions in fertilizer production.

Year Cd [kg] Hg [kg] Pb [kg] TSP [t] PM10 [t] PM2.5 [t]

1990 0.93 0.12 1.17 945 554 292

1995 0.62 0.08 0.77 434 254 134

2000 0.64 0.09 0.80 447 262 138

2005 0.65 0.09 0.81 456 267 141

115 This results in an inconsistency of the time series, as activity data taken from national statistics represent total pro-

duction in Austria, whereas the data obtained from the largest Austrian producer covers only the production of this producer. It is planned to prepare a consistent time series.



Year Cd [kg] Hg [kg] Pb [kg] TSP [t] PM10 [t] PM2.5 [t]

2010 0.65 0.09 0.82 459 269 142

2015 0.65 0.09 0.81 456 267 141

2018 0.50 0.07 0.62 348 204 107

Other processes in organic and inorganic chemical industries

All SO2, NOx and NMVOC process emissions from chemical industries (both organic and inorgan-ic) are reported together as a total in category 2.B.10 Other Chemical Industry. For NOx emis-sions from 1993 onwards, emission data have been split and allocated to the respective emitting processes (ammonia production, fertilizer production and nitric acid production).

Activity data up to 1992 were taken from Statistik Austria. In the year 1997 a study commis-sioned by associations of industries was published (WINDSPERGER & TURI 1997). The activity figures for the year 1993 included in this study were used for all years afterwards, as no more up-to date activity data are available.

Emission data for NOx and CO were taken from the same study (WINDSPERGER & TURI 1997); they were obtained from direct inquiries at the industries. SO2 emissions were re-evaluated by direct inquiries at the industries in 2004. Emissions of this source category are calculated on SNAP level 3 and then aggregated to the NFR category.

NMVOC emissions of this category arise from two large chemical plants. Smaller chemical pro-duction plants are considered in the solvents model, emissions are reported under 2.D.3. Aus-tria is not able to allocate emissions from the large plants to different processes as set out in the 2019 EMEP/EEA Guidebook. For one plant, plant-specific data has been obtained from 1999 onwards (these emissions are below the defined PRTR threshold value). For the second and much larger plant, PRTR data have been included from 2007 onwards. Before 2007, plant-specific data were available for 1996, 2000, 2003. In 1998, an abatement system was installed.

Activity data and emissions for NOx, NMVOC, CO and SO2 from other organic and inorganic chemical industries are presented in Table 230.

Table 230: Activity data and NMVOC, NOx, SO2 and CO emissions from other processes in organic and inorganic chemical industries.

Year Processes in organic chemical industries

Processes in inorganic chemical industries

Activity NMVOC emissions

Activity NOx emissions

SO2 emissions

CO emissions

[t] [t]

1990 461 000 1 618 963 824 4 072 1 565 12 537

1995 473 000 1 618 908 640 IE 712 11 064

2000 482 333 524 908 640 IE 595 11 064

2005 478 427 443 908 640 IE 572 11 064

2010 495 353 569 908 640 IE 497 11 064

2015 519 860 324 908 640 IE 365 11 064

2018 405 103 268 908 640 IE 365 11 064



Chlorine, graphite and per- and trichloroethylene production

Hg emissions from chlorine production are calculated by multiplying production figures from in-dustry by national emission factors (WINDSPERGER et al. 1999) that are based on WINIWARTER & SCHNEIDER (1995). In 1999 the chlorine producing company changed its production process from mercury cell to membrane cell. Therefore, for 1999 the EF was assumed to be half the val-ue of the years before and since 2000 no Hg emissions result from chlorine production.

The production of graphite electrodes constitutes the only graphite production process in Aus-tria. As no emission factor is available for this specific process, PAH emissions from graphite production are not estimated.

HCB emissions and production figures from per- and trichloroethylene production were evaluat-ed in a national study (HÜBNER 2001b). The emission factor used is 60 mg/t product and is based on the study (UMWELTBUNDESAMT BERLIN 1998). From 1993 onwards there is no production of Per- and Trichloroethylene in Austria.

Table 231: Hg and HCB emission factors and emissions from other processes in organic and inorganic chemical industries.

Year Chlorine production Per- Trichloroethylene production

Hg EF [mg/t] Hg emissions [kg] HCB EF [mg/t] HCB emissions [kg]

1990 3000 270 60 1.26

1995 2000 180.00 NO NO

2000 NA NA NO NO

2005 NA NA NO NO

2010 NA NA NO NO

2015 NA NA NO NO

2018 NA NA NO NO


2 B.10.a Other chemical industry

Due to a transcription error NMVOC emissions of one plant have been revised for the whole time series (+ 0.008 kt NMVOC in 2017)

4.4 NFR 2.C Metal Production

In this category, emissions from iron and steel production and casting as well as process emis-sions from non-ferrous metal production and casting are considered.

4.4.1 NFR 2.C.1 Iron and Steel Production


This sub category comprises emissions from blast furnace charging, basic oxygen furnace steel plants, electric furnace steel plants, rolling mills and iron casting operations.



4.4.1.2 Methodological issues

Blast Furnace Charging

In this category, PM, POP and heavy metal emissions are considered. SO2, NOx, NMVOC and CO emissions are included in category 1.A.2.a.

From 1990 to 2000 Heavy metals and POPs (dioxine, HCB) were calculated via multiplying ac-tivity data with emission factors. The emissions factors on process level (sinter, coke oven, blast furnace cowpers) were taken from unpublished national studies (HÜBNER 2001a116), (HÜBNER 2001b117). These emissions on process level have been summed up afterwards. From 2001 on-wards the emissions were calculated by multiplying iron production by the implied emission fac-tors for 2000, except dioxine emissions, which have been reported directly from plant operators since 2002.

Particulate matter emissions for the years 1990 to 2001 were taken from a national study (WINIWARTER et al. 2001). These emissions were taken from environmental declarations from the companies. For the years 2002 onwards, total particulate matter emissions are reported di-rectly by the operator. Emission factors used for PCB are from the EMEP/EEA Emission Inven-tory Guidebook 2016 (EEA 2016).

Pig iron production figures were taken from national statistics. Activity data, POP, HM and PM emissions are presented in Table 232.

Table 232: Activity data (Pig Iron) and emissions from blast furnace charging.

1990 1995 2000 2005 2010 2015 2018

Activity [t] 3 444 000 3 888 000 4 320 000 5 457 755 5 643 855 5 794 527 5 262 843

Emissions [kg]

Cd 342 86 98 124 129 132 120

Hg 218 281 236 298 308 316 287

Pb 26 307 2 118 2 557 3 230 3 340 3 429 3 115

PAH 341 142 139 176 182 186 169

BAP 92 38 38 47 49 50 46

BBF 104 43 42 54 55 57 52

BKF 75 31 30 38 40 41 37

IND 71 29 29 36 38 39 35

Emissions [g] DIOX 33 10 12 2 2 1 1

HCB 7 241 2 261 2 657 3 357 3 472 3 564 3 237

PCB 8 610 9 720 10 800 13 644 14 110 14 486 13 157

Emissions [t] TSP 6 209 4 113 4 174 2 268 849 718 665

PM10 4 346 2 879 2 922 1 587 595 503 466

PM2.5 1 863 1 234 1 252 680 255 215 200

116 according to EUROPEAN COMMISSION IPPC BUREAU (2000); MAGISTRAT DER LANDESHAUPTSTADT LINZ (1995) 117 according to HÜBNER (2000); EUROPEAN COMMISSION IPPC BUREAU (2000); UMWELTBUNDESAMT BERLIN (1998)



Following a recommendation from the last CLRTAP Review, coke input in the sinter plant, coke oven output and blast furnace chowpers, are presented in Table 233.

Table 233: Activity data for the sub processes from 1990, 1995 and 2000.

Year Activity [GJ] sinter coke oven blast furnace cowpers

coke oven input coke oven output blast furnace gas 1990 6 544 261 49 157 826 9 370 000 1995 4 740 138 41 264 751 9 621 911

2000 5 561 462 39 472 500 14 403 000

Basic Oxygen Furnace Steel Plant

In this category, POP and heavy metal emissions are considered. SO2, NOx, NMVOC and CO emissions are included in category 1.A.2.a. PM emissions are reported together with emissions from blast furnace charging.

Emission factors for heavy metal emissions were taken from national studies: 1990–1994 (WINDSPERGER et al. 1999), 1995–2000 (HÜBNER 2001a116), the latter was also used for the years 2001 onwards, and multiplied with steel production to calculate HM emissions. POP emissions were calculated by multiplying steel production by national emission factors (HÜBNER 2001b117) and, for PCB, with emission factors from the EMEP/EEA Emission Inventory Guidebook 2016 (EEA 2016).

Steel production data were taken from national production statistics,Activity data, POP and HM emission factors are presented in the table below; particulate matter emissions are reported to-gether with emissions from blast furnace charging.



Table 234: Activity data, HM and POP emission factors and PM emissions from basic oxygen furnace steel plants.

1990 1995 2000 2005 2010 2015 2018

Activity [t] 3 921 341 4 538 355 5 183

461 6 407

738 6 570 357 7 020 178 6 176 020

Emission factor [mg/t BOF Steel]

Cd 19 13 13

Hg 3 1

1

Pb 984 470 470

PAH 0.04 0.01

0.01

BAP 0.01 0.003 0.003

BBF 0.01 0.004 0.004

BKF 0.01 0.003 0.003

IND 0.01 0.002 0.002

Emission factor [µg/t BOF Steel ]

DIOX 0.69 0.23

0.23

HCB 138 46

46

PCB 2500 2500 2500

Emission factor [g/t BOF Steel ]

TSP IE IE

IE

PM10 IE IE

IE

PM2.5 IE IE

IE

Electric Furnace Steel Plant

Estimation of emissions from electric furnace steel plants was carried out by multiplying produc-tion data by an emission factor. Activity data was provided by the Association for Mining and Steel Industry from 2005 onwards. The emission factors used and their sources are summa-rized in Table 235 together with electric steel production figures.



Table 235: Activity data and emission factors for emissions from Electric Steel Production 1990–2018.

1990 1995 2000 2005 2010 2015 2018

Activity [t] 370 107 453 645 540 539 622 485 637 383 667 000 720 900

Emission factor [g/t Electric steel production]

SO2 590(1) 511(3) 119(3) 40(2)

40(2)

NOx 330(1) 295(3) 119(3) 84(2) 84(2)

NMVOC 70(1)

70(1)

CO 52 000(1) 44 594(3) 7 565(3) 159(2)

159(2)

Emission factor [mg/t Electric steel production]

Cd 80.0(4) 13.0(5) 13.0(5) 0.4(2) 0.4(2)

Hg 75.0(4) 1.0(5)

1.0(5)

Pb 4 125.0(4) 470.0(5) 470.0(5) 19.3(2) 19.3(2)

PAH 13.8(6) 4.6(6)

4.6(6)

BAP 2.1(11) 0.7(11) 0.7(11)

BBF 7.2(11) 2.4(11) 2.4(11)

BKF 2.5(11) 0.8(11) 0.8(11)

IND 1.9(11) 0.6(11) 0.6(11)

Emission factor [µg/t Electric steel production]

DIOX 4.2(6) 1.4(6) 1.4(6) 0.1(2)

0.1(2)

HCB 840.0(6) 280.0(6) 280.0(6) 20.0(2)

20.0(2)

PCB 2500(10)

2500(10)

Emission factor [g/t Electric steel production]

TSP 610.0(7) 610.0(7) 30.0(10)

30.0(10)

PM10 579.5(8) 579.5(8) 28.5(8)

28.5(8)

PM2.5 549.0(9) 549.0(9) 27.0(9)

27.0(9)

Emission factor sources: (1) (WINDSPERGER & TURI 1997), study published by the Austrian chamber of commerce, section industry. This study

reported total VOC and did not distinguish between methane and NMVOC. According to the 2006 IPCC Guidelines (IPCC 2006), chapter 4.2.2.2, VOC emissions in electric steel production consist of NMVOC only. Hence, it was assumed that the VOC emission factor according to this study equals the NMVOC emission factor.

(2) Mean values as reported from industry (Association of Mining and Steel Industries). (3) Interpolated values (expert judgement UMWELTBUNDESAMT). (4) (WINDSPERGER et. al. 1999) (5) (HÜBNER 2001a116) (6) (HÜBNER 2001b117) (7) (EMEP/CORINAIR Emission Inventory Guidebook 2006, EEA 2007) (8) Expert judgement: 95% TSP (9) Expert judgement: 90% TSP



(10)EMEP/EEA Air Pollutant Emission Inventory Guidebook 2016, Chapter 2.C.1 Iron and Steel Production, Page 39, EEA 2016)

(11) Share of the PAH fractions according to the plant specific data of Luxembourg, which were used as no default shares are incluced in guidebook and no PS data from the Austrian plant are available

Rolling Mills

The emission factor for VOC emissions from rolling mills was reported directly by industry and thus represents plant specific data. Similarly to electric steel production, emissions are restricted to NMVOC (i.e. no methane emissions). Hence, it was assumed that VOC emissions equal NMVOC emissions, resulting in an emission factor of 1 g NMVOC/t steel produced.

Steel production data were taken from national production statistics, the amount of electric steel was subtracted.

Iron cast

SO2, NOx, NMVOC and CO emissions were calculated by multiplying iron cast (sum of grey cast iron, cast iron and cast steel) by national emission factors. Activity data were obtained from „Fachverband der Gießereiindustrie Österreichs” (association of the Austrian foundry industry) and one production site, which is since 2015 no longer a member of the association. The emis-sion factors were taken from data published by the Association of the Austrian foundry industry (Fachverband der Gießereiindustrie).

Table 236: Activity data and emission factors for cast iron 1990–2018.

1990 1995 2000 2005 2010 2015 2018

Activity [t] 196 844 176 486 191 420 196 017 167 854 165 193 170 074

Emission factor [g/t Iron cast]

SO2 170 140 140 130 130

NOx 170 160 160 151

151

NMVOC 1 450 1 260 1 260 1 180

1 180

CO 20 020 11 590 11 590 10 843

10 843

Steel Cast

Emission factors for POP emissions were taken from a national study (HÜBNER 2001b). The emis-sion factors used are 4.6 mg PAH per t cast iron, 0.03 µg Dioxine per t cast iron and 6.4 µg HCB per t cast iron. Heavy metal emissions were calculated by multiplying national emission factors (1990–1994: WINDSPERGER et. al. 1999; 1995 onwards: HÜBNER 2001a) by the same activity data used for POP emissions. The emission factors used are 1 mg Hg per t cast iron, 80 mg Cd (1990: 110 mg) per t cast iron and 2 g Pb (1990: 4.6 g) per t cast iron. Activity data until 1995 is taken from a national study (HÜBNER 2001b). From 1996 onwards, data published by the Asso-ciation of the Austrian foundry industry (Fachverband der Gießereiindustrie) has been used.

Ferroalloys

An emission factor for TSP (1 kg/t Alloy) was taken from the EMEP/EEA Emission Inventory Guidebook 2019 (EEA 2019), emission factors for PM10 and PM2.5 are based on expert judge-ment (PM10 95% TSP, PM2.5 90%; same as for electric steel production).



4.4.2 NFR 2.C.2 – 2.C.6 Non-ferrous Metals


In this category, process emissions from non-ferrous metal production as well as from non-ferrous metal cast (light metal cast and heavy metal cast) are considered.

4.4.2.2 Methodological issues

Non-ferrous Metals Production

POP emissions from aluminium production were estimated in a national study (HÜBNER 2001b) and were 6 090 kg PAH and 0.002 g Dioxine in 1990. Primary Aluminium production in Austria was terminated in 1992.

The Pb emission factor for secondary aluminium production is based on the following regula-tions/assumptions:

(i) TSP emissions from aluminium production is legally limited to 20 mg/m³ (BGBl. II 1/1998 for Al),

(ii) as the facilities have to be equipped with PM filters to reach this limit, the emissions are usually well below the legal emission limit,

(iii) thus PM emissions were estimated to be 5 mg/m³; (iv) using results from BAT documents (0.25% Pb content in PM; 126–527 mg PM/t Al; UMWELTBUNDESAMT 2000b) and (EUROPEAN COMMISSION, IPPC BUREAU 2000) an emission factor of 200 mg/t Al was calcu-lated.

The 2016 EMEP/EEA Guidebook emission factors were used for PM and PCB. In 1997, a fabric filter was installed on the production site; therefore the emissions of the filterable pollutants were calculated with the default abatement efficiency (99%) from the 2016 EMEP/EEA Guide-book.

Production data on secondary aluminium production are confidential.

Secondary lead is produced by two companies which use lead accumulators and plumbiferous metal ash as secondary raw materials. Lead recuperation is processed in rotary furnaces.

Emissions from secondary lead production (2.C.5) were calculated from national data (BMWFW 2016) using national emission factors (HÜBNER 2001a) and emission factors from the EMEP/EEA Emission Inventory Guidebook 2016 (EEA 2016) for PCB and PM. In order to avoid any double counting all SO2 emissions are allocated to NFR category 1.A.2.b.

For secondary copper production the emission factors were taken from the EMEP/EEA GB 2016 for PM, PCB and SOx. EFs for HM, HCB and Dioxin were taken from national studies (HÜBNER 2001a). For the years from 2004 onwards abatement factors were applied for HM, PM and Diox-in.

Non-ferrous Metals Casting Activity data were obtained from „Fachverband der Gießereiindustrie Österreichs” (association of the Austrian foundry industry). The applied emission factors as presented below were taken from a study commissioned by the same association (Fachverband der Gießereiindustrie) and from direct information from this association.



Table 237: Activity data and emission factors for non-ferrous (light metal) cast 1990–2018.

1990 1995 2000 2005 2010 2015 2018

Activity [t] 46 316 59 834 92 695 109 927 121 426 140 749 150 559

Emission factor [g/t light metal cast]

SO2 120 10

10

NOx 330 230 230 170

170

NMVOC 4 040 1 740 1 740 1 289

1 289

CO 2 340 880 880 660 660

Table 238: Emission factors and activity data for heavy metal cast 1990–2018.

1990 1995 2000 2005 2010 2015 2018

Activity [t] 8 525 10 384 13 214 18 456 16 577 12 814 12 853

Emission factor [g/t heavy metal cast]

SO2 100 80

80

NOx 100 80

80

NMVOC 1 390 1 180

1 180

CO 3 290 2 770

2 770


In this year’s submission estimates for the PAH fractions BAP, BBF, BKF, IND category 2.C.1 has been included.

4.5 NFR 2.D.3-2.G Solvents and other Product use

This chapter describes the methodology used for calculating air emissions from Solvent and Other Product Use in Austria. Solvents are chemical compounds which are used to dissolve substances as paint, glues, ink, rubber, plastic, pesticides or for cleaning purposes (degreasing). After application of these substances or other procedures of solvent use most of the solvents are released into air. Because solvents consist mainly of NMVOC, solvent use is a major source for anthropogenic NMVOC emissions in Austria. Once released into the atmosphere NMVOCs react with reactive molecules (mainly HO-radicals) or high energetic light to finally form CO2.

Besides NMVOC further air pollutants from solvent use are relevant: Cd and Pb from NFR Sector 2.D.3.g Chemical products, as well as PAH, dioxins and HCB from NFR Sector 2.D.3.i Preservation of wood. PM from NFR 2.G Other (Fireworks and Tobacco Smoking)



The following activities are covered by NFR sector 2.D.3-G:

NFR category Description

2.D.3.a Domestic solvent use including fungicides

2.D.3.b Road paving with asphalt

2.D.3.c Asphalt roofing

2.D.3.d Coating application

2.D.3.e Degreasing

2.D.3.f Dry cleaning

2.D.3.g Chemical Products

2.D.3.h Printing

2.D.3.i Other solvent use

2.D.3.g Asphalt blowing

2.G Other product use

4.5.1 Emission Trends

In the year 2018, 28% of total NMVOC emissions in Austria (30.13 kt) originated from Solvent and Other Product Use. Table 239 presents the trend in NMVOC emissions by subcategories.

Table 239: Total NMVOC emissions and trend from 1990–2018 by subcategories of category 2.D.3 Solvent and Other Product Use.

NFR codes 2.D.3 2.D.3.a 2.D.3.b 2.D.3.c 2.D.3.d 2.D.3.e 2.D.3.f 2.D.3.g 2.D.3.h 2.D.3.i

year kt NMVOC

1990 114.44 16.30 0.01 NE 45.79 13.26 0.44 12.79 12.65 13.20

1995 81.28 20.36 0.01 NE 26.72 8.18 0.37 7.42 9.26 8.95

2000 58.80 18.91 0.01 NE 16.67 6.51 0.29 4.78 5.42 6.22

2001 56.90 18.62 0.01 NE 15.91 6.49 0.27 4.50 4.94 6.16

2002 55.99 18.00 0.01 NE 14.96 6.38 0.25 4.18 6.16 6.04

2003 55.39 17.70 0.02 NE 13.23 5.42 0.37 5.46 7.93 5.26

2004 46.64 14.91 0.02 NE 9.94 3.87 0.41 5.59 8.06 3.85

2005 54.22 17.47 0.02 NE 10.29 3.75 0.56 7.51 10.81 3.81

2006 60.15 19.67 0.02 NE 10.14 3.39 0.71 9.33 13.42 3.48

2007 58.84 19.69 0.02 NE 8.77 2.60 0.76 9.97 14.37 2.66

2008 55.65 19.23 0.02 NE 7.29 1.81 0.77 10.12 14.64 1.76

2009 44.71 16.24 0.02 NE 6.05 1.50 0.57 7.70 11.18 1.45

2010 43.41 16.62 0.02 NE 6.08 1.51 0.50 7.01 10.23 1.45

2011 42.48 17.21 0.02 NE 6.17 1.54 0.42 6.34 9.31 1.46

2012 40.52 17.45 0.02 NE 6.14 1.53 0.34 5.49 8.12 1.43

2013 35.64 16.39 0.02 NE 5.65 1.41 0.23 4.26 6.38 1.31



NFR codes 2.D.3 2.D.3.a 2.D.3.b 2.D.3.c 2.D.3.d 2.D.3.e 2.D.3.f 2.D.3.g 2.D.3.h 2.D.3.i

year kt NMVOC

2014 33.44 16.52 0.02 NE 5.57 1.39 0.14 3.37 5.14 1.27

2015 29.94 16.00 0.02 NE 5.28 1.32 0.05 2.36 3.72 1.19

2016 28.93 15.46 0.02 NE 5.10 1.28 0.05 2.28 3.59 1.15

2017 30.46 16.27 0.02 NE 5.37 1.35 0.05 2.40 3.79 1.21

2018

30.13 16.10 0.02 NE 5.31 1.33 0.05 2.38 3.74 1.20

Trend 1990– 2018

-73,67%

-1,23% 273.29

%

-88.40%

-89.97%

-89.12%

-81.42%

-70.41%

-90.91%

Share in National Total

1990 35.46% 6.08% 0.00% - 13.71% 3.97% 0.13% 3.83% 3.79% 3.95%

2018 28.10% 15.01% 0.02% - 4.95% 1.24% 0.04% 2.22% 3.49% 1.12%

NMVOC emissions in this sector decreased by 74% between 1990 and 2018, due to technolog-ical improvement also resulting from the enforced laws and regulations in Austria: In the early 1990ies the VOC content of products such as paints, varnishes, preservatives and glues was limited in Austria, the use of CKWs and Benzol was largely prohibited, the content of aromatic compounds limited and measures for installations applying VOC containing products were set: Solvent Ordinance (1991)118 (repealed by Solvent Ordinance 1995) Solvent Ordinance 1995119 (repealed by Solvent Ordinance 2005) Paint finishing systems Ordinance (1995)120 (repealed by VOC Installations Ordinance)

In the subsequent years the legislation was adapted to be in line with European legislation: VOC Installations Ordinance (2002)121, implementation of “Solvent Emission Directive”122 VOC Ordinance 2005123 – implementation of “Paints Directive”124 118 Verordnung des Bundesministers für Umwelt, Jugend und Familie über Verbote und Beschränkungen von organi-

schen Lösungsmitteln (Lösungsmittelverordnung), BGBl. Nr. 492/1991 119 Verordnung des Bundesministers für Umwelt über Verbote und Beschränkungen von organischen Lösungsmitteln

(Lösungsmittelverordnung 1995 – LMVO 1995), BGBl 872/1995 120 Verordnung des Bundesministers für wirtschaftliche Angelegenheiten über die Begrenzung der Emission von luft-

verunreinigenden Stoffen aus Lackieranlagen in gewerblichen Betriebsanlagen (Lackieranlagen-Verordnung), BGBl. Nr. 873/1995

121 Verordnung des Bundesministers für Wirtschaft und Arbeit zur Umsetzung der Richtlinie 1999/13/EG über die Be-grenzung der Emissionen bei der Verwendung organischer Lösungsmittel in gewerblichen Betriebsanlagen (VOC-Anlagen-Verordnung – VAV) BGBL II Nr. 301/2002

122 Council Directive 1999/13/EC of 11 March 1999 on the limitation of emissions of volatile organic compounds due to the use of organic solvents in certain activities and installations

123 Verordnung des Bundesministers für Land- und Forstwirtschaft, Umwelt und Wasserwirtschaft über die Begrenzung der Emissionen flüchtiger organischer Verbindungen durch Beschränkung des Inverkehrsetzens und der Verwen-dung organischer Lösungsmittel in bestimmten Farben und Lacken (Lösungsmittelverordnung 2005 – LMV 2005), BGBl. II Nr. 398/2005



Amendment of VOC Ordinance (2005) 125 – implementation of “Industrial Emissions Directive” 2010/75/EC126

Measures implemented in emission intensive activity areas such as coating, painting and print-ing as well as in the pharmaceutical industry range from primary measures such as substitution of solvents, reduction of solvent contents and shift to lower or non-solvent emitting processes to secondary measures which basically is waste gas treatment.

4.5.2 NMVOC Emissions from Solvent and other product use (Category 2.D.3.a-i)


Emissions are estimated using a combination of Top-down data from national statistics which provide information on the overall solvent use in

Austria with bottom-up information from inquires in solvent consuming sectors, and after 2000, infor-

mation from company solvent balances in solvent consuming sectors. The model used for the calculation of NMVOC emissions from solvents use was established for the year 2000. It is based on a top-down and bottom-up approach: top-down data is based on statistical data and their average solvent contents, bottom-up data used for the allocation of the different amounts to the respective SNAP categories is based on data and information from sol-vent using industry, scaled up (if needed) using employee numbers or expert judgements. Fur-thermore additional investigations as e.g. for domestic solvent use, were used. The model was finalized in 2003. Since then, statistical allocations was changed a few times, solvent contents were regulated by different legislations (e.g. Eco Paint Directive, etc.), especially the Solvent Emissions or VOC directive (and the subsequent Industrial Emissions Directive), which de-mands minimum abatement techniques from different industrial sectors. In order to take these changes into account, the following main revisions have been introduced in the years 2016-2019: 1. Statistical data used for the calculation of the Top Down Sum, i.e. the overall amount of sol-

vents placed on the market, has been reviewed: changes in statistical data were taken into account, some redundant posts were deleted, some new ones taken into account, some “non-solvent” uses were updated (these are substances that are not emitted during or after use, as they are used as a reagent for synthesis).

2. Solvent contents for products, especially for the domestic use, were reviewed, and solvent contents and emission factors from the German UBA, based on data directly from producers were taken into account The German and Austrian markets are very much alike, thus this approach is the most feasible.

124 Directive 2004/42/EC of the European Parliament and of the Council of 21 April 2004 on the limitation of emissions

of volatile organic compounds due to the use of organic solvents in decorative paints and varnishes and vehicle re-finishing products and amending Directive 1999/13/EC

125 Verordnung des Bundesministers für Land- und Forstwirtschaft, Umwelt und Wasserwirtschaft, mit der die Lö-sungsmittelverordnung 2005 geändert wird (Änderung der Lösungsmittelverordnung 2005), BGBl. II Nr. 25/2013

126 Directive 2010/75/EU of the European Parliament and of the Council of 24 November 2010 on industrial emissions (integrated pollution prevention and control)



3. Bottom-up data was completely reviewed, based on solvent balances reported by industry: solvent balances were collected for those companies that are required to report their solvent use as well as solvent emissions in the course of the VOC Installations Ordinance (2002). They were then allocated to their respective SNAP category. For those categories, where not all installations were covered by the reporting obligation (because their solvent consumption does not exceed the defined threshold), the number of employees working in these compa-nies was investigated, and emissions were scaled to the total number of employees for that sector taken from statistics..

Together with the institute that elaborated the former model, these data and the information at hand were incorporated for 2015 to be consistent to the data and the model for 2002. Data in between was interpolated. For a more detailed description of the model update please refer to the IIR 2019, chapter .5.2.1. Due to the intensity of preparation and details needed, updates of the bottom up data are planned every 5 years, this means that solvent balances will be collected in 2021 for the year 2020, using this information AD allocation will be revised and EFs will be updated; Furthermore the top-down sum (changes in statistical allocation etc) will be reviewed. For the years in be-tween only the top down sum will be updated; allocation of the activity data as well as the emis-sion factors from the year 2015 will be used.

Top down data:

Data from national import/export and production statistics provide a balance for substances used as solvents and solvents contained in products:

Solvent Balance per Substancei = (Substancei Import – Substancei Export + Substancei Pro-duction)

From the Solvent Balance per Substance (or substance group, respectively) the non-solvent use of substances (i.e. where the substance is used as a reagent) is subtracted:

Solvent Use per Substancei = Solvent Balance per Substancei – Non Solvent Use of Sub-stancei

“Non solvent use” of a substance is any use of a substance where it is not emitted, i.e. sub-stances (or a certain share of the substances) used as a reagent in a chemical processes,

For products containing solvents, such as paints and glues, a balance of imports and exports is made, and the solvent content is estimated. The production of solvent containing products is not accounted for in this equation, as the amount of solvents used for their production are already accounted for in the above mentioned balance based on substance (groups):

Solvents in Productp = (Solvent-containing Productp Import – Solvent-containing Productp Ex-port)* Solvent content of Productp

The overall solvent use in Austria is then calculated as the sum of the balances per substance and the amounts of solvents contained in products imported and exported:

Overall solvent use in Austria = ∑i Solvent Use per Substancei + ∑p Solvents in Productp



Bottom up data

For 1990–2002:

Extensive inquiries concerning solvent applications were made in several studies in the 90ies (WINDSPERGER et al. 2002a/2002b/2004/2008): for a reference year (2000) and several other years (1980, 1990, 1995, 2003) and the amount of solvents consumed in the different sub cate-gories was estimated.

In a first step an extensive survey on the use of solvents in the year 2000 was carried out in 1 300 Austrian companies (WINDSPERGER et al. 2002b). In this survey data about the solvent content of paints, cleaning agents etc. and on solvents used (both substances and substance categories) like acetone or alcohols were collected. Furthermore information were gathered about:

type of application of the solvents final application, cleaner, product preparation;

type of waste gas treatment open application, waste gas collection, waste gas treatment.

For every category of application and waste gas treatment an emission factor was estimated to calculate solvent emissions in the year 2000 (see Table 240).

Table 240: Emission factors for NMVOC emissions from Solvent Use.

Category Factor

final application 1.00

cleaner 0.85

product preparation 0.05

open application 1.00

waste gas collection 0.50

waste gas treatment 0.20

The above mentioned survey was carried out in all industrial branches with solvent applications; results for solvent use per substance category were collected at NACE-level-4. The total amounts of solvents used per industrial branch were extrapolated using the number of employ-ees (the values of “solvent use per employee” of the sample was multiplied by total employment of the relevant branches taken from national employment statistics (STATISTIK AUSTRIA 2000 & 1998) and using information from (KSV1870 INFORMATION 2000).

For three years (1980, 1990, 1995) the values for solvent use were extrapolated using the factor “solvent use per employee” of the year 2000 and the number of employees of the respective year taken from national statistics (Statistik Austria 2001) (WINDSPERGER et al. 2004). For the pillar year 2005 the structural business statistics (number of employees (NACE Rev.1.1)) were taken from (EUROSTAT 2008).



In a second step a survey in 1 800 households was conducted (WINDSPERGER et al. 2002a) for estimating the domestic solvent use (37 categories in 5 main groups: cosmetic, do-it-yourself, household cleaning, car, fauna and flora). Also, solvent use in the context of moonlighting be-sides commercial work and do-it-yourself was calculated.

The comparison of top down and bottom up approach helped to identify several additional ap-plications that contribute to a large extent to the total amount of solvents used. Thus in a third step the quantities of solvents used in these applications such as windscreens wiper fluids, anti-freeze, hospitals, de-icing agents of aeroplanes, tourism, cement- respectively pulp industry, were estimated in surveys.

The outcome of these three steps was the total stock of solvents used for each application in the year 2000 (at SNAP level 3) (WINDSPERGER et al. 2002a). To achieve a time series the de-velopment of the economic and technical situation in relation to the year 2000 was considered. It was distinguished between “general aspects” and “specific aspects”. The information about these defined aspects were collected for three pillar years (1980, 1990, 1995) and were taken from several studies (SCHMIDT et al. 1998, BARNERT 1998) and expert judgements from associations of industries (chemical industry, printing industry, paper industry) and other stakeholders. On the basis of this information calculation factors were estimated. With these factors and the data for solvent use and emission of 2000 data for the years 1980, 1990 and 1995 was estimated. For the years in between data was linearly interpolated.

For 2003 onwards:

In 2015–2018, for the 2015 new data and methods were applied, and data from 2003-2015 was interpolated. Mainly data available from reports under directive 1999/13/EC (VOC Solvents Di-rective)127 were implemented into the model:

An extensive research was based on solvent balances for the year 2015 of those companies that were obliged to report their use of solvents as well as emissions under directive 1999/13/EC (VOC Solvents Directive). The companies were then allocated to the different SNAPs, and the number of employees was surveyed. The total number of employees of the whole sector was derived from the national statistic on performance and structures (Österreichische Leistungs- und Strukturstatistik), which was then adjusted to the part of the sector in question (based on expert judgement). With the proportion of the employees of the companies to the total number of the sector, activity data as well as emissions were calculated for each SNAP. In some cases, for those sectors where discrepancies between smaller and bigger enterprises were too big, a form factor was introduced to reflect a plausible relation.

Two exceptions from that approach were taken for the following sectors:

Domestic use: the amount of products on the Austrian market were taken into account, infor-mation on solvent content and emission factors from German UBA were obtained and used. Activity data is the amount of solvents in products, which were combined with the respective emission factor for each type of product (which led to a combined EF of 74% for Domestic Solvent Use (Other), and 95% for Domestic Use of Pharmaceuticals). Emission factors were also interpolated between the old and new approach, with the help of IIÖ.

Paints used in construction, as well as domestic use: statistical data was combined with in-formation on the average solvent content of paints derived from studies on the Ecopaint di-rective. Activity data reflects the solvent content of paints and not the amount of paints used, an emission factor of 95% is applied.

127 VOC-Anlagen-Verordnung (VAV), BGBl. II Nr. 301/2002 vom 26.7.2002



Top down/bottom up combination Data from the top down approach (for the reference year 2000, up to 2002 as well as 2015) were compared with data from the /bottom up approach. As there where large discrepancies the sub sectors were further investigated and identified additional sources added to the bottom up approach, additional identified non-solvent uses subtracted from the top down approach. As a deviation of 10-20% remained, the bottom up data was adjusted to finally fit the (higher) top down sum. The following graph depicts the logic behind the calculation of NMVOC emissions in Austria:

Figure 45: Sankey diagram of the calculation of solvent emissions in Austria (WINDSPERGER et al. 2018).

4.5.2.2 Activity data

Activity data have been updated since the last submission. Activity data for 2.D.3 solvent use consists of the amount of solvents placed on the market in Austria, minus the amount of “non-solvent use” (see chapter on methodological issues for a description of data used.

Table 241: Activity data for solvent and other product use [t] 1990–2018.

2.D.3 2.D.3.a 2.D.3.d 2.D.3.e 2.D.3.f 2.D.3.g 2.D.3.h 2.D.3.i

Year t Solvent

1990 137 924 23 361 50 131 15 467 459 18 585 14729 15 192

1995 130 088 25 296 50 371 13 564 426 12 465 13 474 14 492

2000 112 872 21 896 35 517 11 940 340 23 798 8 242 11 140

2001 112 709 21 698 35 281 12 210 340 24 073 7 960 11 148

Quelle: WINDSPERGER et al. 2018



2.D.3 2.D.3.a 2.D.3.d 2.D.3.e 2.D.3.f 2.D.3.g 2.D.3.h 2.D.3.i

Year t Solvent

2002 114 039 21 112 34 638 12 342 337 24 023 10 557 11 031

2003 113 487 20 896 30 772 10 936 545 26 156 14 503 9 680

2004 97 164 17 719 23 063 8 168 645 24 633 15 798 7139

2005 115 698 20 894 23 558 8 306 980 31 994 22 830 7 135

2006 132 473 23 691 22 512 7 887 1 364 39 676 30 735 6 609

2007 134 842 23 877 18 379 6 378 1 634 43 479 35 954 5 141

2008 133 910 23 477 13 755 4 698 1 867 46 245 40 336 3 532

2009 113 829 19 957 11 692 3 993 1 587 39 310 34 287 3 002

2010 117 341 20 572 12 053 4 116 1 636 40 523 35 345 3 095

2011 122 370 21 454 12 569 4 293 1 706 42 260 36 860 3 228

2012 124 912 21 900 12 830 4 382 1 741 43 138 37 626 3 295

2013 118 181 20 720 12 139 4 146 1 648 40 813 35 598 3 117

2014 119 891 21 029 12 321 4208 1 672 41 367 36 131 3 164

2015 116 913 20 507 12 014 4 103 1 631 40 339 35 233 3 085

2016 112 960 19814 11 608 3 965 1 576 38 975 34 042 2 981

2017 118 940 20 863 12 223 4 174 1 659 41 039 35 844 3 139

2018 117 643 20 635 12 090 4 129 1 641 40 591 35 453 3 105

Also emission factors have been updated since the last submission. They were evaluated taking into account information from actual solvent balances from companies in the respective sector. EFs for 2015 are based on this evaluation, and were interpolated to 2002, taking into account information from each economic sector, expert judgements and legal obligations (as well as BATs).

According to an encouragement from the CLRTAP review in 2017, IEFs are also presented on a g/person per year basis for 2.D.3.a, Domestic Solvent use for 2018 and are as follows:

SNAP 060408 1 356 g NMVOC/person per year

SNAP 060411 451 g NMVOC/person per year

Table 242: Implied NMVOC Emission factors for Category 3 Solvent and Other Product Use 1990–2018.

2.D.3.a 2.D.3.d 2.D.3.e 2.D.3.f 2.D.3.g 2.D.3.h 2.D.3.i

EF

1990 0.91 0.90 0.81 0.95 0.81 0.86 0.76

1995 0.91 0.70 0.58 0.88 0.78 0.69 0.67

2000 0.90 0.65 0.52 0.85 0.47 0.66 0.65

2001 0.89 0.64 0.50 0.80 0.44 0.62 0.64

2002 0.89 0.63 0.49 0.74 0.41 0.58 0.63

2003 0.89 0.61 0.47 0.69 0.43 0.55 0.62

2004 0.88 0.60 0.45 0.63 0.40 0.51 0.61

2005 0.88 0.58 0.43 0.58 0.38 0.47 0.60

2006 0.87 0.57 0.41 0.52 0.35 0.44 0.59

2007 0.87 0.56 0.40 0.47 0.32 0.40 0.59



2.D.3.a 2.D.3.d 2.D.3.e 2.D.3.f 2.D.3.g 2.D.3.h 2.D.3.i

EF

2008 0.87 0.54 0.38 0.41 0.29 0.36 0.51

2009 0.86 0.53 0.36 0.36 0.26 0.33 0.50

2010 0.86 0.51 0.34 0.30 0.23 0.29 0.49

2011 0.86 0.50 0.33 0.25 0.20 0.25 0.47

2012 0.85 0.48 0.31 0.19 0.17 0.22 0.46

2013 0.85 0.47 0.29 0.14 0.14 0.18 0.45

2014 0.85 0.46 0.27 0.08 0.13 0.14 0.44

2015 0.84 0.44 0.25 0.03 0.09 0.11 0.43

2016 0.84 0.44 0.25 0.03 0.09 0.11 0.43

2017 0.84 0.44 0.25 0.03 0.09 0.11 0.43

2018 0.84 0.44 0.25 0.03 0.09 0.11 0.43

4.5.3 NFR 2.D.3.b., 2.D.3.c. and 2.D.3. g - NMVOC Emissions related to Asphalt

In this chapter the following sectors related to asphalt producing and processing are included 2.D.3.b Road paving with asphalt 2.D.3.c: Asphalt roofing 2.D.3.g Asphalt blowing During the development of the updated model on solvent emissions in Austria in 2018, these processes have also been investigated and revised.

2.D.3.b Road paving with asphalt The emissions caused by road paving with asphalt were formerly calculated within the solvents model. During the refinement of this sector it became visible, that these production processes related to NMVOC couldn’t be caused by solvent use as these emissions result from the product itself. So, the default values of the EMEP EEA GB 2016 have been applied for calculating NMVOC emissions. The operation conditions were proven via personal conversation with Gestrada (Austrian Association for Asphalt). Activity data were obtained for the whole time series from the national production statistics. PM2.5 emissions will be estimated for the next submission.

Table 243: Activity data and NMVOC emissions from road paving with asphalt.

Year Activity NMVOC emissions

[t] 1990 402 727 6.0 1995 522 418 7.8 2000 429 292 6.4 2005 1 304 864 19.6 2010 1 414 091 21.2 2015 1 314 188 19.7 2017 1 353 548 20.3 2018 1 503 348 22.6



2.D.3.c Asphalt roofing This subsector has been investigated during the evaluation of the solvents model. There are four production sites of asphalt roofing material in Austria. Currently all of these production sites have gas collection systems and gas purification units (e.g. thermal afterburner). However, further investigation is necessary in order to provide a robust time series, ,so for the current submission the notation key of this category has been changed to NE.

2.D.3.g Asphalt blowing In Austria there are only 2 asphalt blowing plants. One is part of the only Austrian refinery and therefore the emissions are included in NFR category 1.A.1.b (petroleum refinery) . The off gas of the second asphalt blowing plant is treated in a fluidized bed burner (with an exhaust gas pu-rification unit), these emissions are negligible. Emissions are therefore reported as “IE”.

4.5.4 Emissions from Other Product Manufacture and Use (Category 2.G)

The category 2.G covers emissions which originate from the use of fireworks and tobacco.

2.G other use (Use of fireworks (SNAP 0604))

2.G other use (Use of tobacco (SNAP 0604))

Key category Pb (for 2.G total)

Pollutant SO2, CO, NOx, TSP, PM10, PM2.5, Cd, Hg, Pb

CO, NOx,NMVOC, NH3, TSP, PM10, PM2.5, Cd,

Dioxin, PAH

Activity Amount of fireworks placed on market

Inhabitants (Smokers)

Method EMEP/EEA 2016 default emission factors used.

Emission factor EMEP/EEA 2016 default emission factors used

Recalculation Recalculation, as new emission factors were used.

For emissions from fireworks, the amount of fireworks placed on the market was used (im-port+production – export) as activity data. For tobacco use, the amount of cigarettes sold in Austria was used. In 2018, more accurate data on cigarettes, loose tobacco and cigars became available from the Ministry of Finance. Thus, the time series was adapted according to the new information. According to the EMEP/EEA Guidebook, 1g of tobacco per cigarette and 5g of to-bacco per cigar was assumed.

Table 244: Emissions from SNAP 0604_X6A Fireworks from 1990–2018.

NFR 2.G Use of Fireworks

SO2 NOx CO Cd Hg Pb TSP PM10 PM2.5

years [t] 1990 4.71 0.41 11.14 0.002 0.0001 1.22 171.18 155.73 80.95

1995 4.19 0.36 9.93 0.002 0.0001 1.09 152.46 138.71 72.10

2000 6.45 0.56 15.26 0.003 0.0001 1.67 234.48 213.32 110.89

2001 4.06 0.35 9.62 0.002 0.0001 1.05 147.77 134.43 69.88

2002 6.38 0.55 15.10 0.003 0.0001 1.66 231.94 211.01 109.69

2003 5.53 0.48 13.08 0.003 0.0001 1.43 200.99 182.85 95.05



NFR 2.G Use of Fireworks

SO2 NOx CO Cd Hg Pb TSP PM10 PM2.5

years [t] 2004 5.35 0.46 12.66 0.003 0.0001 1.39 194.47 176.92 91.97

2005 6.03 0.52 14.28 0.003 0.0001 1.57 219.35 199.56 103.74

2006 6.72 0.58 15.91 0.003 0.0001 1.75 244.47 222.41 115.61

2007 6.77 0.58 16.02 0.003 0.0001 1.76 246.11 223.90 116.39

2008 6.75 0.58 15.97 0.003 0.0001 1.75 245.34 223.20 116.02

2009 5.59 0.48 13.24 0.003 0.0001 1.45 203.42 185.07 96.20

2010 5.75 0.49 13.60 0.003 0.0001 1.49 208.93 190.08 98.81

2011 6.34 0.55 15.01 0.003 0.0001 1.65 230.53 209.73 109.02

2012 5.72 0.49 13.55 0.003 0.0001 1.49 208.19 189.41 98.46

2013 6.19 0.53 14.65 0.003 0.0001 1.61 224.97 204.67 106.39

2014 5.32 0.46 12.60 0.003 0.0001 1.38 193.62 176.15 91.57

2015 2.89 0.25 6.85 0.001 0.0001 0.75 105.18 95.69 49.74

2016 4.56 0.39 10.79 0.002 0.0001 1.18 165.81 150.85 78.41

2017 3.54 0.31 8.39 0.002 0.0001 0.92 128.86 117.23 60.94

2018 3.20 0.28 7.59 0.002 0.0001 0.83 116.51 106.00 55.10

Table 245: Emissions from SNAP 604_X6B Tobacco Use from 1990–2018

NFR 2.G Tobacco Use

NOx CO NH3 NMVOC Cd TSP PM10 PM2.5 PAH Diox

years [t] [t] [t] [t] [t] [t] [t] [t] [kg] [mg]

1990 30.32 928.27 69.91 81.54 90.97 454.87 454.87 454.87 4.14 1.68

1995 29.00 887.76 66.86 77.98 87.00 435.02 435.02 435.02 3.96 1.63

2000 29.08 890.30 67.06 78.20 87.25 436.26 436.26 436.26 3.97 1.62

2001 28.77 880.78 66.34 77.37 86.32 431.60 431.60 431.60 3.93 1.60

2002 29.04 888.89 66.95 78.08 87.11 435.57 435.57 435.57 3.97 1.61

2003 28.17 862.35 64.95 75.75 84.51 422.57 422.57 422.57 3.85 1.57

2004 27.35 837.26 63.06 73.55 82.05 410.27 410.27 410.27 3.74 1.52

2005 25.53 781.41 58.85 68.64 76.58 382.91 382.91 382.91 3.49 1.42

2006 26.64 815.33 61.41 71.62 79.91 399.53 399.53 399.53 3.64 1.48

2007 26.19 801.69 60.38 70.42 78.57 392.84 392.84 392.84 3.58 1.45

2008 25.49 780.14 58.76 68.53 76.46 382.28 382.28 382.28 3.48 1.42

2009 26.10 799.05 60.18 70.19 78.31 391.55 391.55 391.55 3.57 1.45

2010 26.94 824.56 62.10 72.43 80.81 404.05 404.05 404.05 3.68 1.50

2011 25.48 780.11 58.76 68.53 76.45 382.27 382.27 382.27 3.48 1.42

2012 25.54 781.90 58.89 68.68 76.63 383.14 383.14 383.14 3.49 1.42

2013 25.62 784.19 59.06 68.88 76.85 384.27 384.27 384.27 3.50 1.42

2014 25.37 776.59 58.49 68.22 76.11 380.54 380.54 380.54 3.47 1.41

2015 25.10 768.48 57.88 67.50 75.31 376.57 376.57 376.57 3.43 1.39

2016 24.74 757.23 57.03 66.52 74.21 371.06 371.06 371.06 3.38 1.37

2017 24.48 749.28 56.43 65.82 73.43 367.16 367.16 367.16 3.35 1.36

2018 23.51 719.72 54.21 63.22 70.54 352.68 352.68 352.68 3.21 1.31




NFR 2.D.3.a Solvent Use

Following in depth QC activities time series inconsistencies in the solvents model were re-moved: (i) the reporting categories of the import/export statistics for various ethers had changed over time and were now considered consistently and (ii) for antifreeze fluids, of which not all reported in the category are relevant for VOC emission, the same assumption as used in the years before was applied. This led to a decrease of NMVOC emissions of 6.25 kt in 2017.

2.D.3.Domestic Solvent Use, Hg emissions

Due to the omission of the EF for Hg from the EMEP EEA GB 2019, this source is no longer re-ported.

NFR 2.G Tobacco Use and emissions from firework use:

More detailed information became available from the Austrian Ministry of Finance, based on the amount of cigarettes, as well as loose tobacco products and cigars taxed in Austria fromz on-wards. The trend was then extrapolated back to 1990. This led to an increase of emissions of NOx, CO, NMVOC, NH3, TSP, PM10, PM2.5, Cd, Ni, Zn, Cu, Dixon and PAHs.



4.6 NFR 2.H Other processes

This category covers emissions in the food and beverages industry. Emissions from 2.H.1 are included 1.A.2.d.

4.6.1 NFR 2.H.2 Food and Beverages Industry


This category includes NMVOC emissions from the production of bread, wine, spirits and beer and PM emissions from the production of beer. Furthermore this category includes POP emis-sions from smokehouses.


NMVOC emissions were calculated by multiplying the annual production by an emission factor. The following emission factors were applied: Bread ...... ..4 200 gNMVOC/tbread Wine ....... ..65 gNMVOC/hlwine Beer ........ ..20 gNMVOC/hlbeer Spirits ..... ..2 000 gNMVOC/hlspirit

All emission factors were taken from BUWAL (1995) because of the very similar structures and standards of industry in Austria and Switzerland. Activity data were taken from national statistics (Statistik Austria). For the year 2008 no activity data are available, therefore the values of 2007 were also used for 2008.

PM emissions from beer production correspond to fugitive emissions from barley used for the production of malt. Emissions were estimated in a national study (WINIWARTER et al. 2001) and amounted to: TSP1990: 2.2 t, 1995: 2.1 t, 1999–2005: 1.9 t PM10........ 1990: 1.1 t, 1995: 1.0 t, 1999–2005: 0.9 t PM2.5 ....... 1990: 0.5 t, 1995: 0.3 t, 1999–2005: 0.3 t

POP emissions from smokehouses were estimated in an unpublished study (HÜBNER 2001b128) that evaluates POP emissions in Austria from 1985 to 1999. The authors of this study calculated POP emissions using technical information on smokehouses and the number of smokehouses from literature (WURST & HÜBNER 1997), (MEISTERHOFER 1986). The amount of smoked meat was also investigated by the authors of this study. From 2000 onwards the emission values of 1999 have been used as no updated emissions are available. Activity data and emissions are presented in Table 246.

128 according to MEISTERHOFER (1986)



Table 246: POP emissions and activity data from smokehouses 1990–2018:

Year Activity [t] Emissions

Smoked meat

PAH [kg]

BAP [kg] BBF [kg] BKF [kg] IND [kg] Diox [g] HCB [g]

1990 15 318 545 191 175 66 112 1.8 358

1995 19 533 107 38 34 13 22 0.4 72

2000 19 533 37 13 12 5 8 0.1 26

2018 19 533 37 13 12 5 8 0.1 26


In this year’s submission an estimate of the PAH fractions BAP, BBF, BKF, IND in Sector 2.H.2 has been included.

4.7 NFR 2.I Wood Processing

4.7.1 Source Category Description

This category includes particulate matter emissions from supply (production) and handling of wood-chips and sawmill-by-products for the use in chipboard and paper industry and for the use in combustion plants.

The following subcategories are included: Generic wood processing Supply and handling of wood chips and sawmill by-products for the use in chipboard and pa-

per industry (split into two sub-categories) Use of wood chips and sawmill by-products in chipboard production Supply and handling of wood chips and sawmill by-products for use in combustion plants Gaseous emissions from chipboard production are reported under category 2.H.1.

4.7.2 Methodological Issues

The methodology for emission calculation was developed in a national study (WINIWARTER et al. 2007) and emissions were calculated for 2001 applying emission factors of a Swiss study (EMPA 2004) to Austrian activities. Two major sources are identified: the sawmill industry including wood-processing and the chipboard industry.



Generic wood processing

For generic wood processing, the method developed by WINIWARTER et al. (2007) resulted in the following combined emission factors: TSP: 149.5 g/scm; PM10: 59.8 g/scm; PM2.5: 23.92.G/scm; applied to an activity of 4 Mio solid cubic metres (scm). Due to lack of activity data these values were used for the whole time-series.

Supply and handling of wood chips and sawmill by-products for the use in chipboard and paper industry

For this category, WINIWARTER et al. (2007) provided two distinct sets of emission factors for the following two situations: Wood chips produced on-site Wood chips and sawmill by-products acquired from off-site production

For the former situation, the mass of wood logs acquired and processed on-site was used as activity data. The same activity data was used for all years. Activity data and emission factors are shown in the following table.

Table 247: Activity data (used for all years) and emission factors for supply and handling of wood-chips and sawmill by-products for the use in chipboard and paper industry.

Produced on-site

wood chips-industry-logs

Produced off-site

wood chips-industry-byproduct

Emission factor [g/t]

TSP 30.0 20.0

PM10 12.0 8.0

PM2.5 4.8 3.2

Use of wood chips and sawmill by-products in chipboard production

For chipboard production, emissions were calculated by a factor based on a national study (WINIWARTER et al. 2007, p 41). With these emissions an implied emission factor was calculated using chipboard production data from national statistics (Statistik Austria) that was applied to the whole time-series of chipboard production. Emissions of particulate matter (TSP, PM10 and PM2.5) caused by the product handling are also included in this source.

Supply and handling of wood chips and sawmill by-products for use in combustion plants

For supply and handling of wood chips and sawmill by-products for use in combustion plants, an implied emission factor was calculated using gross consumption of wood waste in the national energy balance that was applied to the whole time-series.



Table 248: Activity data and emissions for supply (production) and handling of wood-chips and sawmill by-products for the use in combustion plants.

Year Wood waste – gross consumption [TJ]

Emissions [t]

TSP PM10 PM2.5

1990 11 788 25.81 10.32 4.13

1995 12 595 27.58 11.03 4.41

2000 29 982 65.65 26.26 10.50

2005 51 666 113.12 45.25 18.10

2010 97 256 212.94 85.18 34.07

2015 102 319 224.03 89.61 35.84

2018 97 248 212.92 85.17 34.07


NFR 2.I Wood processing Due to recalculations of the energy balances, reported particular matter emissions since 2005 have changed. (-0.001 kt PM2.5 for 2017).

Austria’s Informative Inventory Report (IIR) 2020 – Agriculture (NFR Sector 3)


5 AGRICULTURE (NFR SECTOR 3)

5.1 Sector Overview

This chapter includes information on the estimation of NH3, NOx, NMVOC, SO2, CO, particulate matter (PM), heavy metals (HM) and persistent organic pollutant (POP) of the sector Agriculture in Austria corresponding to the data reported in category 3 of the NFR format. It describes the cal-culations of source categories 3.B Manure Management, 3.D Agricultural Soils and 3.F Field Burning of Agricultural Residues.

For some pollutants the agricultural sector is only a minor source: emissions of SO2, CO, heavy metals and POPs arise only from the categories 3.D.f Use of pesticides and 3.F Field burning of agricultural wastes; the contribution to the national total is low (0% - 4%).

To give an overview of Austria's agricultural sector some information is provided below (accord-ing to the 2010 Farm Structure Survey – full survey and the Agriculture Structure Surveys 2013 and 2016) (BMNT 2000–2019): Agriculture in Austria is rather small-structured: 162 018 farms are managed, 56.9% of these farms manage less than 20 ha, whereas only 5.5% of the Austri-an farms manage more than 100 ha cultivated area. 128 164 holdings are classified as situated in less favoured areas. Related to the federal territory Austria has the highest share of moun-tainous areas in the EU (70%).

The agricultural area comprises 2.67 million hectares that is a share of ~ 32% of the total territo-ry (forestry ~ 41%, other area ~ 14%). The shares of the different agricultural activities are as follows: 50% arable land, 22% grassland (meadows mown several times and seeded grassland), 26% extensive grassland (meadows mown once, litter meadows, rough pastures, alpine pas-

tures and mountain meadows), 2% other types of agricultural land-use (vineyards, orchards, house gardens, vine and tree

nurseries).


5.2.1 Completeness

Table 238 gives an overview of the NFR categories included in this chapter and presents the transformation matrix from SNAP categories. It also provides information on the status of emis-sion estimates of all subcategories. A „” indicates that emissions from this sub-category have been estimated.



Table 249: Overview of sub-categories of agriculture and status of estimation.

NFR Category NEC gas CO PM Heavy metals

POPs

NO

x

NM

VOC

SO2

NH

3

CO

TSP

PM10

PM2.

5

Cd

Hg

Pb

Dio

xin

PAH

HC

B

PCB

3.B. MANURE MANAGEMENT NA NA NA NA NA NA NA NA NA

3.B.1 Cattle NA NA NA NA NA NA NA NA NA 3.B.1.a Dairy Cattle NA NA NA NA NA NA NA NA NA 3.B.1.b Non-Dairy Cattle NA NA NA NA NA NA NA NA NA

3.B.2 Sheep NA NA NA NA NA NA NA NA NA 3.B.3 Swine NA NA NA NA NA NA NA NA NA 3.B.4 Other Livestock NA NA NA NA NA NA NA NA NA Buffalo NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO Goats NA NA NA NA NA NA NA NA NA Horses NA NA NA NA NA NA NA NA NA Mules and asses1) IE IE IE IE IE IE IE IE IE IE IE IE IE IE IE Laying hens NA NA NA NA NA NA NA NA NA Broilers NA NA NA NA NA NA NA NA NA Turkeys NA NA NA NA NA NA NA NA NA Other poultry NA NA NA NA NA NA NA NA NA Other Animals NA NA NA NA NA NA NA NA NA 3.D AGRICULTURAL

SOILS NA NA NA NA NA NA NA NA NA

3.D.a.1 Inorganic N fertilizers NA NA NA NA NA NA NA NA NA NA NA NA NA 3.D.a.2 Organic N fertilizers NA NA NA NA NA NA NA NA NA NA NA NA 3.D.a.2.a Animal manure applied

to soils NA NA NA NA NA NA NA NA NA NA NA NA

3.D.a.2.b Sewage sludge applied to soils NA NA NA NA NA NA NA NA NA NA NA NA NA

3.D.a.2.c Other organic fertilisers applied to soils (including compost)

NA NA NA NA NA NA NA NA NA NA NA NA NA

3.D.a.3 Urine and dung deposited by grazing animals

IE NA NA NA NA NA NA NA NA NA NA NA NA

3.D.a.4 Crop residues NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA 3.D.b Indirect emissions from

managed soils NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO

3.D.c Farm-level agricultural operations including storage, handling and transport of agricultural products


3.D.d Off-farm storage, handling and transport of bulk agricultural products


3.D.e Cultivated crops NA NA NA NA NA NA NA NA NA NA NA NA NA NA 3.D.f Use of pesticides NO NO NO NO NO NO NO NO NO NO NO NO NO NO 3.F FIELD BURNING OF

AGRICULTURAL RESIDUES

NA

3.I Agriculture other NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO

1) included in 3.B.4 Horses




Austria’s key category analysis is presented in Chapter 1.5. This chapter includes information on the agriculture sector. Key sources within this category are presented in Table 239.

Table 250: Key sources of sector Agriculture.

NFR Category Source Categories Key Categories Pollutant KS-Assessment

3.B.1 Manure Management (Cattle) NH3 LA, TA 3.B.1 Manure Management (Cattle) NMVOC LA, TA 3.B.3 Manure Management (Swine) NH3 LA, TA 3.D.a.1 Inorganic N-fertilizers NH3 LA, TA 3.D.a.2 Organic fertilizers NH3 LA, TA 3.D.a.2 Organic fertilizers NOx LA, TA 3.D.a.2 Organic fertilizers NMVOC LA, TA 3.D.c On-farm storage, handling and

transport of agricultural products TSP LA, TA

3.D.c On-farm storage, handling and transport of agricultural products

PM10 LA, TA

LA = Level Assessment (if not further specified – for the years 1990 and 2018)

TA = Trend Assessment 1990–2018

5.2.3 Methodology

The Austrian sectorial inventory model follows the N-flow concept. NH3 emissions are calculated on the basis of the amount of total ammoniacal nitrogen (TAN). TAN is present in the urine of animals and considered to be equivalent to the N content of urine. This calculation method is more precise than the calculation on the basis of total N excretion because emissions of NH3 arise from TAN. The calculation addresses both N pools (N excretion and TAN) for the different stages of manure management (housing storage spreading) in terms of NH3, NOx, N2O and N2 (storage) emissions and includes information of the total N amount within each relevant stage (N excretion), and the fraction of that amount that is present as TAN.

Table 240 includes a summary of the methodologies used in Austria’s agriculture sector as rec-ommended in the CLRTAP Review report for Austria 2010 (UNITED NATIONS, 2010).

Table 251: Summary of methodologies used in Austria’s agriculture inventory.

NFR category Methodology used 3.B Manure Management

3.B.1 Cattle T3 (NH3), T2 (NOx, NMVOC), T1 PM)

3.B.2 Sheep T2 (NH3, NOx, NMVOC), T1 (PM) 3.B.3 Swine T3 (NH3), T2 (NOx, NMVOC), T1

PM) 3.B.4 Other Livestock T2 (NH3, NOx, NMVOC), T1 (PM)

3.D Agricultural Soils

3.D.a.1 Inorganic N fertilizers T3 (NH3), T1 (NOx) 3.D.a.2.a Animal manure applied to soils T3 (NH3), T2 (NMVOC), T1 (NOx) 3.D.a.2.b Sewage sludge applied to soils T1 3.D.a.2.c Other organic fertilisers applied to soils (including compost)

T1

3.D.a.3 Urine and dung deposited by grazing animals T3 (NH3), T2 (NMVOC)



NFR category Methodology used 3.D.c Farm-level agricultural operations including storage, handling and transport of agricultural products

T1

3.D.d Off-farm storage, handling and transport of bulk agricultural products

T1 (country-specific)

3.D.e Cultivated crops T2

3.F Field Burning of agricultural Residues T1

The following table presents an overview of the country specific data used in the agriculture in-ventory including a short indication on the sources for this data.

Table 252: Information on country specific data used in sector agriculture.

NFR category Parameter Source 3.B Manure Management

3.B (all livestock) MMS distribution AMON & HÖRTENHUBER (2010), AMON & HÖRTENHUBER (2019)

3.B (cattle, swine, chicken, horses) Anaerobic digestion AMON (2002), E-CONTROL (2008, 2011, 2013, 2017, 2018, 2019)

3.B (all livestock) N excretion

PÖTSCH (2005), GRUBER & PÖTSCH (2006), STEINWIDDER & GUGGENBERGER (2003), UNTERARBEITSGRUPPE N-ADHOC (2004) UND ZAR (2004), BMLFUW (2017)

3.D. Agricultural Soils

Austria’s N-flow model Country-specific consideration of N-losses

(AMON et al. 2002, 2008, 2010, 2014 & 2019)

Sewage sludge spreading Compost application

N content data N content data

UMWELTBUNDESAMT (1997) Expert judgement by UMWELTBUNDESAMT (2015)


The following chapter gives an estimate of uncertainties with respect to NOx, NH3, NMVOC, SO2

and PM2.5 emissions from animal manures, agricultural soils as well as field burning of agricul-tural soils. Overall uncertainties result from uncertainties in the activity data and from uncertain-ties in the emission factors.

Activity data Uncertainties of cattle and swine numbers were re-evaluated in submission 2016. Uncertainties were derived by analysing official Austrian livestock numbers published in June and December each year. Comparing these two data sets the standard deviation was calculated. As a con-servative approach the doubled standard deviation was taken, leading to an uncertainty for dairy cattle of 2%, for non-dairy cattle of 1% and for swine of 4%.

Emission factors Emission factors are rated based on the qualitative assessment (see Chapter 1.7, Table 25).

Table 242 presents uncertainties for emissions (for selected pollutants) as well as for activity da-ta used in sector agriculture according to the error propagation method (Tier 1).



Table 253: Uncertainties of emissions in sector 3 Agriculture for selected pollutants.


[%]

NH3 Emissions

[%]

NMVOC Emissions

[%]

SO2 Emissions

[%]

PM2.5 Emissions

[%]

3.B.1 Manure Management (Cattle)

+/-125.0% +/-20.0% +/-125.0% NA +/-200.0%

3.B.2 Manure Management (Sheep)

+/-125.4% +/-41.2% +/-125.4% NA +/-200.2%

3.B.3 Manure Management (Swine)

+/-125.1% +/-20.4% +/-125.1% NA +/-200.0%

3.B.4 Manure Management (Other animals)

+/-125.4% +/-41.2% +/-125.4% NA +/-200.2%

3.D.a. Agricultural Soils +/-125.1% +/-40.3% +/-125.1% NA +/-200.1%

3.D.c On-farm storage NA NA NA NA +/-200.1%

3.D.d Off-farm storage NA NA NA NA +/-200.1%

3.D.e Cultivated Crops NA NA +/-750.0% NA NA

3.F Field Burning +/-160.1% +/-160.1% +/-160.1% +/-160.1% +/-160.1%

Activity Data

Animal Population - Cattle +/-1%

Animal Population - Swine +/-4%

Animal Population – Sheep and Other

+/-10%

Area Data & Fertilizer Input (combined)

+/-5%


The following sector specific QA/QC procedures have been carried out: 1) Activity data check Check for transcription errors, comparison with published data (BMNT 2000–2019), Consistency checks of sub-categories with totals, Plausibility checks of dips and jumps;

2) Emission factors Comparison with EMEP/EEA default values and factors reported by other countries;

3) Calculation by spreadsheets Consistent use of livestock characterization, Cross-checks through all steps of calculation, Documentation of sources and correct use of units;

4) Results (emissions) Check of recalculation differences, Plausibility checks of dips and jumps;

5) Documentation Findings and corrections marked in the spreadsheets, Improvement list (internal and external findings).



In the Austrian QMS regularly extensive QA and verification activities are carried out (Tier 2 QA).

In 2012 Agriculture was validated. Some minor inconsistencies with respect to the MMS data have been found and corrected.

In 2014 an external review by Austrian Agricultural experts within the framework of a stakehold-er meeting was held. Reason was the revision of the Austrian inventory model for sector agricul-ture according to the 2006 IPCC GL and the EMEP/EEA GB 2013. Applied values and parame-ters were discussed and validated by the national experts.

In 2018 the agricultural model was revised as new data on the agricultural practice in Austria became available with the TIHALO II study (PÖLLINGER et al. 2018) as well as due to improve-ments of the N-flow according to the EMEP/EEA GB 2016. Within the framework of this revision a stakeholder meeting (so-called “inventory talks”) was held in order to discuss applied values, parameters, time series and study results with Austrian agricultural experts (UMWELTBUNDESAMT 2010, 2014 & 2018).

A general description of Austria’s QMS (Quality Management System) is presented in Chapter 1.6.


It is planned to evaluate the national N excretion values on the basis of a new scientific study. The project will be carried out by the University of Natural Resources and Applied Life Science (BOKU) and will start in spring 2020.

5.3 NFR 3.B Manure Management

The Austrian sectorial inventory model follows the N-flow concept (AMON & HÖRTENHUBER 2014, AMON & HÖRTENHUBER 2019). In the current submission Austria included the recommendations under the NEC Review 2019 as well as implemented the new EMEP/EEA GB 2019.

Data on animal husbandry and manure management systems all over Austria are based on the following surveys: (KONRAD 1995), TIHALO I (AMON et al. 2007) and TIHALO II (PÖLLINGER et al. 2018).


NH3 emissions from Sector 3 Agriculture are estimated according to the EMEP/EEA Air Pollu-tant Emission Inventory Guidebook (EEA 2019). Emissions from cattle and swine are estimated using a country specific methodology which requires detailed information on animal characteris-tics and the manner in which manure is managed. NH3 emissions from the non-key animal cat-egories sheep, goats, poultry, horses and deer have been estimated using the detailed Tier 2 method following the EMEP/EEA Guidebook 2019. The Tier 2 method follows a mass flow anal-ysis, which is more detailed and thus better reflects Austrian conditions.

Sector manure management is not a key category for NOx emissions. However, the calculations are based on the Tier 2 methodology provided in the EMEP/EEA Guidebook 2019 (EEA 2019).



Following a recommendation under the NEC Review 2018 (EC 2018), Austria applied the Tier 2 methodology for NMVOC emissions from manure management which has been identified as a key source for category cattle (3.B.1). The enhanced methodology has been used for all live-stock categories.

Animal numbers The Austrian official statistics (STATISTIK AUSTRIA 2019b) provides national data of annual live-stock numbers on a very detailed level. These data are based on livestock counts held in De-cember each year129.

Table 243 and Table 244 presents applied animal data. Background information listed below: From 1990 onwards: The continuous decline of dairy cattle numbers is connected with the in-

creasing milk yield per cow: For the production of milk according to Austria’s milk quota every year a smaller number of cows is needed.

1991: A minimum counting threshold for poultry was introduced. Farms with less than 11 poul-try were not considered any more. However, the contribution of these small farms is negligible, both with respect to the total poultry number and to the trend. The increase of the soliped population between 1990 and 1991 is caused by a better data collection from riding clubs and horse breeding farms.

1993: New characteristics for swine and cattle categories were introduced in accordance with Austria’s entry into the European Economic Area and the EU guidelines for farm animal population categories. In 1993 part of the “Young cattle < 1 yr” category was included in the “Young cattle 1–2 yr” category. This shift is considered to be insignificant: no incon-sistency in the emission trend of “Non-Dairy Cattle” category was recorded. In the same year “Young swine < 50 kg” were shifted to “Fattening pigs > 50 kg” (before 1993 the limits were 6 months and not 50 kg which led to the shift) causing distinct in-consistencies in time series. Following a recommendation of the Centralized Review 2003, the age class split for swine categories of the years 1990–1992 was adjusted us-ing the split from 1993.

1993: For the first time other animals e.g. deer (but not wild living animals) were counted. Fol-lowing the recommendations of the Centralized Review 2004, to ensure consistency and completeness animal number of 1993 was used for the years 1990 to 1992.

1995: The financial support of suckling cow husbandry increased significantly in 1995 when Austria became a Member State of the European Union. The husbandry of suckling cows is used for the production of veal and beef; the milk yield of the cow is only pro-vided for the suckling calves. Especially in mountainous regions with unfavourable farm-ing conditions, suckling cow husbandry allows an extensive and economic reasonable utilisation of the pastures. Suckling cow husbandry contributes to the conservation of the traditional Austrian alpine landscape.

1996–1998: The market situation affected a decrease in veal and beef production, resulting in a declining suckling cow husbandry. Farmers partly used their former suckling cows for milk production. Thus, dairy cow numbers slightly increased at this time. Reasons are manifold: Changing market prices, BSE epidemic in Europe and change of consumer behaviour, milk quota etc.

1998–2000; 2006–2008: increasing/ decreasing swine numbers: The production of swine has a high elasticity to prices: Swine numbers are changing due to changing market prices very rapidly. Market prices change due to changes in costumer behaviour, saturation of swine production, epidemics etc.

129 For cattle livestock counts are also held in June, but seasonal changes are very small (between 0% and 2%). Live-

stock counts of sheep are only held in December (sheep is only a minor source for Austria and seasonal changes of the population are not considered relevant).



Table 254: Domestic livestock population and its trend 1990–2018 (I).

Year Livestock category – Population size [heads] * Dairy Non-Dairy Suckling

Cows Young Cattle

< 1 yr Breeding Heifers 1–2 yr

Fattening Heifers,

Bulls, Oxen 1–2 yr

Other Cattle > 2 yr

1990 904 617 1 679 297 47 020 925 162 255 464 305 339 146 312 1991 876 000 1 658 088 57 333 894 111 253 522 301 910 151 212 1992 841 716 1 559 009 60 481 831 612 239 569 281 509 145 838 1993 828 147 1 505 740 69 316 705 547 257 939 314 982 157 956 1994 809 977 1 518 541 89 999 706 579 263 591 309 586 148 786 1995 706 494 1 619 331 210 479 691 454 266 108 298 244 153 046 1996 697 521 1 574 428 212 700 670 423 259 747 277 635 153 923 1997 720 377 1 477 563 170 540 630 853 259 494 254 986 161 690 1998 728 718 1 442 963 154 276 635 113 254 251 241 908 157 415 1999 697 903 1 454 908 176 680 630 586 255 244 233 039 159 359 2000 621 002 1 534 445 252 792 655 368 246 382 220 102 159 801 2001 597 981 1 520 473 257 734 658 930 241 556 214 156 148 097 2002 588 971 1 477 971 244 954 640 060 236 706 213 226 143 025 2003 557 877 1 494 156 243 103 641 640 229 150 216 971 163 292 2004 537 953 1 513 038 261 528 646 946 230 943 210 454 163 167 2005 534 417 1 476 263 270 465 628 426 229 874 206 429 141 069 2006 527 421 1 475 498 271 314 631 529 222 104 212 887 137 664 2007 524 500 1 475 696 271 327 634 089 211 044 226 014 133 222 2008 530 230 1 466 979 266 452 636 469 200 787 230 457 132 814 2009 532 976 1 493 284 264 547 643 441 196 476 249 486 139 334 2010 532 735 1 480 546 260 883 634 052 187 386 256 266 141 959 2011 527 393 1 449 134 256 831 623 364 184 160 245 770 139 009 2012 523 369 1 432 249 248 438 628 715 184 932 238 968 131 196 2013 529 560 1 428 722 236 655 626 970 191 002 243 546 130 549 2014 537 744 1 423 457 229 986 629 401 191 049 241 408 131 613 2015 534 098 1 423 512 224 348 624 483 194 493 244 588 135 600 2016 539 867 1 414 524 216 678 632 150 192 455 239 588 133 653 2017 543 421 1 400 055 207 007 623 517 190 364 248 227 130 940 2018 532 873 1 379 935 200 475 618 218 188 698 239 685 132 859 Trend 90–18

-41.1% -17.8% 326.4% -33.2% -26.1% -21.5% -9.2%

The FAO agricultural data base (FAOSTAT) provides worldwide harmonized data (FAO AGR. STATISTICAL SYSTEM 2001). In the case of Austria, these data come from the national statistical system (Statistik Austria). However, there are inconsistencies between these two data sets. Analysis shows that there is often a time gap of one year between the two data sets. FAOSTAT data are seemingly based on the official Statistik Austria data but there is an annual attribution error. In the Austrian inventory Statistik Austria data is used, they are the best available.



Table 255: Domestic livestock population and its trend 1990–2018 (II).

Year Livestock category – Population size [heads] * Swine Young &

Fattening Pigs >8 kg

Breeding Sows

> 50 kg

Young Swine < 20 kg

litter <8kg3)

litter 8-20kg4)

Sheep Goats Horses1) Other (furred

game)**2) 1990 3 687 981 2 797 564 382 335 958 645 508 082 450 563 309 912 37 343 49 200 37 100 1991 3 637 980 2 759 635 377 152 945 648 501 193 444 454 326 100 40 923 57 803 37 259 1992 3 719 600 2 821 549 385 613 966 864 512 438 454 426 312 000 39 400 61 400 37 418 1993 3 819 798 2 894 886 396 001 997 945 528 911 469 034 333 835 47 276 64 924 37 577 1994 3 728 991 2 822 077 394 938 965 992 511 976 454 016 342 144 49 749 66 748 37 736 1995 3 706 185 2 802 410 401 490 947 707 502 285 445 422 365 250 54 228 72 491 40 323 1996 3 663 747 2 759 957 398 633 953 126 505 157 447 969 380 861 54 471 73 234 41 526 1997 3 679 876 2 777 680 397 742 951 800 504 454 447 346 383 655 58 340 74 170 56 244 1998 3 810 310 2 911 469 386 281 967 094 512 560 454 534 360 812 54 244 75 347 50 365 1999 3 433 029 2 631 875 343 812 862 910 457 342 405 568 352 277 57 993 81 566 39 086 2000 3 347 931 2 561 396 334 278 853 315 452 257 401 058 339 238 56 105 82 943 39 612 2001 3 440 405 2 629 403 350 197 869 443 460 805 408 638 320 467 59 452 84 319 40 138 2002 3 304 650 2 530 789 341 042 816 640 432 819 383 821 304 364 57 842 85 696 40 664 2003 3 244 866 2 494 399 334 329 785 166 416 138 369 028 325 495 54 607 87 072 41 190 2004 3 125 361 2 388 397 317 033 792 323 419 931 372 392 327 163 55 523 89 816 42 102 2005 3 169 541 2 449 640 315 731 762 585 404 170 358 415 325 728 55 100 92 560 43 014 2006 3 139 438 2 404 507 321 828 779 440 413 103 366 337 312 375 53 108 95 304 43 926 2007 3 286 292 2 545 838 318 349 796 424 422 105 374 319 351 329 60 487 98 048 44 839 2008 3 064 231 2 372 683 297 830 742 865 393 718 349 147 333 181 62 490 100 792 45 751 2009 3 136 967 2 440 474 293 901 759 607 402 592 357 015 344 709 68 188 103 536 46 663 2010 3 134 156 2 444 258 284 691 764 542 405 207 359 335 358 415 71 768 106 280 47 575 2011 3 004 907 2 348 549 275 874 717 895 380 484 337 411 361 183 72 358 109 024 45 654 2012 2 983 158 2 338 990 263 200 718 808 380 968 337 840 364 645 73 212 111 768 43 733 2013 2 895 841 2 278 627 254 373 684 606 362 841 321 765 357 440 72 068 114 512 41 812 2014 2 868 191 2 254 177 246 870 692 725 367 144 325 581 349 087 70 705 117 256 41 600 2015 2 845 451 2 233 618 249 655 683 354 362 178 321 176 353 710 76 620 120 000 41 388 2016 2 792 803 2 201 953 240 756 660 555 350 094 310 461 378 381 82 735 120 000 41 176 2017 2 820 082 2 222 453 243 694 667 802 353 935 313 867 401 480 91 134 130 000 41 176 2018 2 776 574 2 197 904 232 714 652 748 345 956 306 792 406 336 91 536 130 000 41 176 Trend 90–18

-24.7% -21.4% -39.1% -31.9% -31.9% -31.9% 31.1% 145.1% 164.2% 11.0%

* from 1990 to 1992 adjusted age class split for swine as recommended in the centralized review (October 2003) ** furred game, mainly deer. 1) for the years 2000–2002 and 2004–2014: interpolated values 2) for the years 1991–1993, 2000-2002, 2004–2009 and 2011–2012: interpolated values 3) share of litter < 8 kg within young swine category < 20 kg (53%, STATISTIK AUSTRIA 2018d) 4) share of litter 8–20 kg within young swine category < 20 kg (47%, STATISTIK AUSTRIA 2018d)

Swine numbers decreased in 2018 compared to the previous year. For sheep and goats a rise in livestock numbers could be observed in 2018.



In response to a recommendation under the NEC Review 2018 (EC 2018), Austria splitted the piglets numbers < 20 kg into suckling piglets < 8 kg and weaned piglets 8–20 kg. The share of suckling and weaned piglets was calculated on the basis of daily weight gain and official live-stock data (STATISTIK AUSTRIA 2018d). This approach was accepted under the NEC Review 2018 and applied for all inventory years.

Horse numbers for 2015, 2016, 2017 and 2018 are provided by the Ministry of Agriculture and are published in (BMNT 2000–2019, p. 49). Horse numbers used for the years before 2004 are based on livestock accountings and are assessed to be representative for Austria. Data for the years 2004 to 2014 were derived by interpolation.

Table 256: Domestic livestock population and its trend 1990–2018 (III).

Year Livestock category – Population size [heads] *

Total Poultry Chicken* Laying hens*

Broilers* Turkeys** Other Poultry**

1990 13 820 961 13 139 151 8 392 369 4 746 782 524 616 157 194 1991 14 397 143 13 478 820 8 340 068 5 138 752 759 307 159 016 1992 13 683 900 12 872 100 7 853 673 5 018 427 671 215 140 585 1993 14 508 473 13 588 850 8 307 661 5 281 189 793 431 126 192 1994 14 178 834 13 265 572 8 288 140 4 977 432 781 643 131 619 1995 13 959 316 13 157 078 7 899 011 5 258 067 679 477 122 761 1996 12 979 954 12 215 194 7 387 086 4 828 108 642 541 122 219 1997 14 760 355 13 949 648 7 894 150 6 055 498 693 010 117 697 1998 14 306 846 13 539 693 7 193 505 6 346 188 645 262 121 891 1999 14 498 170 13 797 829 6 786 341 7 011 488 585 806 114 535 2000 11 786 670 11 077 343 6 555 815 4 521 528 588 522 120 805 2001 12 571 528 11 905 111 6 974 146 4 930 965 547 232 119 185 2002 12 571 528 11 905 111 6 974 146 4 930 965 547 232 119 185 2003 13 027 145 12 354 358 6 525 623 5 828 735 550 071 122 716 2004 13 258 183 12 577 852 6 602 159 5 975 692 559 463 120 869 2005 13 489 222 12 801 345 6 678 696 6 122 650 568 854 119 022 2006 13 720 260 13 024 839 6 755 232 6 269 607 578 246 117 175 2007 13 951 298 13 248 332 6 831 768 6 416 564 587 638 115 328 2008 14 182 336 13 471 826 6 908 304 6 563 521 597 030 113 481 2009 14 413 375 13 695 319 6 984 841 6 710 479 606 421 111 634 2010 14 644 413 13 918 813 7 061 377 6 857 436 615 813 109 787 2011 15 020 126 14 305 565 7 373 407 6 932 158 610 708 103 853 2012 15 395 838 14 692 317 7 685 438 7 006 879 605 602 97 919 2013 15 771 551 15 079 069 7 997 468 7 081 601 600 497 91 985 2014 16 334 620 15 634 432 8 356 808 7 277 624 597 071 103 117 2015 16 897 690 16 189 796 8 716 148 7 473 648 593 645 114 249 2016 17 460 759 16 745 159 9 075 488 7 669 671 590 219 125 381 2017 17 460 759 16 745 159 9 075 488 7 669 671 590 219 125 381 2018 17 460 759 16 745 159 9 075 488 7 669 671 590 219 125 381 Trend 90–18

26.3% 27.4% 8.1% 61.6% 12.5% -20.2%

* interpolated values for the years 2004-2009 and 2011-2012 ** value for 1999 is not available – value derived from the average share of previous and following 5 years of total oth-

er poultry; interpolated values for the years 2004-2009 and 2011-2012



Animal numbers of Poultry and Other (furred game) are not included in the livestock counts held in December each year but gathered within Austria’s farm structure surveys carried out as com-plete surveys every 10 years (next in 2020).

5.3.2 NH3 emissions from cattle (3.B.1) and swine (3.B.3)

Key Category: NH3

5.3.2.1 Agricultural practice – cattle and swine

Manure Management System Distribution (MMS)

MMS data used in the national inventory is based on the following national surveys on agricul-tural practices (KONRAD 1995, AMON et al. 2007 and PÖLLINGER et al. 2018). The research pro-ject ‘Animal husbandry and manure management systems in Austria (TIHALO I)’ (AMON et al. 2007) has been carried out as a comprehensive survey on the agricultural practices in Austria. Within this project, the Division of Agricultural Engineering (DAE) of the Department for Sustain-able Agricultural Systems of the University of Natural Resources and Applied Life Sciences (BOKU) closely co-operated with the Swiss College of Agriculture, the Austrian Chamber of Ag-riculture, the Umweltbundesamt, the Agricultural Research and Education Centre Raumberg-Gumpenstein and the Statistics Austria. The statistical sampling plan (5 000 Austrian farms, re-turn rate of 39%) was set up with the assistance of the Statistics Austria to guarantee the selec-tion of a representative sample.

As a result of TIHALO I, for the year 2005 updated representative data on animal husbandry and manure management systems all over Austria was available. For the year 1990 MMS data based on (KONRAD 1995) was used. In this study data on existing Austrian conditions were de-rived from a research survey carried out on 720 randomly-chosen agricultural enterprises in the years 1989–1992.

In 2017 the TIHALO I study has been followed-up by a new research project (TIHALO II) (PÖLLINGER et al. 2018). For this project, as for the previous one, a comprehensive survey on the agricultural practices in Austria has been carried out. 5 000 questionnaires were sent to the farmers and a return rate of 37% could be achieved. Compared to the first TIHALO study, the questionnaire for the farmers was additionally available as an online version, which was used by more than 50% of the participants. The new study was conducted by the Agricultural Research and Education Centre Raumberg-Gumpenstein as lead, but in close cooperation with the Austri-an Chamber of Agriculture, the Federal Institute of Agricultural Economics, the Federal Ministry for Sustainability and Tourism and the Umweltbundesamt. So, for 2017 new information on live-stock feeding, management systems and practices as well as application techniques in Austria became available.

For the creation of a plausible time series the MMS distribution of 1990 (based on KONRAD 1995) partly had to be adapted. Changes to the year 1990 were derived from the TIHALO I and TIHALO II study results and expert opinion (DI Alfred Pöllinger, Agricultural Research and Edu-cation Centre Raumberg-Gumpenstein) carried out in (AMON & HÖRTENHUBER 2019). Thus, MMS data are available for 1990 (Konrad), 2005 (TIHALO I) and 2017 (TIHALO II). The years in between were derived by interpolation and for 2018 the values of 2017 have been used. Infor-mation on anaerobic digestion is based on data published by the Austrian Energy Regulator (E-CONTROL 2019). 1990 data are based on (AMON 2002).



For the livestock categories sheep, poultry, horses, goats and deer country specific MMS data has been applied. Data are based on the TIHALO II results (PÖLLINGER et al. 2018) and expert judgement (PÖLLINGER 2018), carried out in (AMON & HÖRTENHUBER 2019). Except for chicken, the MMS distribution of these animal categories has been kept constant over the entire time se-ries.

Table 257: Share of N in manure management systems 1990 (cattle and swine).

Animal category Manure Management Systems 1990

Buildings – tied systems Buildings – loose housing systems

Excreted outside the buildings

liquid slurry [%]

solid manure [%]

liquid slurry [%]

solid manure [%]

yards [%]

pasture [%]

Dairy cows 23.6 50.4 11.0 3.4 0.9 10.7

Suckling cows 12.3 58.7 6.0 11.3 1.1 10.7

Cattle < 1 year 11.3 53.3 6.8 23.0 0.8 4.8

Breeding heifers 1–2 years

17.5 39.5 9.4 6.7 0.8 26.2

Fattening heifers, bulls & oxen, 1–2 years

30.4 37.3 18.2 12.8 0.8 0.6

(other) cattle > 2 years

20.6 44.9 9.2 6.6 1.0 17.8

Breeding sows plus litter

-- -- 69.2 29.7 1.2 --

Fattening pigs -- -- 71.3 28.2 0.6 --

For yards the values for the year 1990 were estimated to be the half of the values from 2005 (PÖLLINGER 2008).


Animal category Manure Management Systems 2005

Buildings – tied systems Buildings – loose housing systems

Excreted outside the buildings

liquid slurry [%]

solid manure [%]

liquid slurry [%]

solid manure [%]

yards [%]

pasture [%]

Dairy cows 13.4 49.9 23.4 7.3 1.8 4.2

Suckling cows 6.1 45.1 11.4 21.6 2.1 13.7

Cattle < 1 year 4.6 30.8 13.8 46.8 1.6 2.4


9.9 40.1 22.9 16.4 1.5 9.2


12.2 24.4 36.1 25.5 1.5 0.3


12.5 42.0 20.2 14.5 1.9 8.9


-- -- 60.0 37.7 2.3 --

Fattening pigs -- -- 88.2 10.7 1.1 --




Animal category Manure Management Systems 2017 Buildings – tied systems Buildings – loose housing

systems Excreted outside the

buildings liquid slurry

[%] solid manure

[%] liquid slurry

[%] solid manure

[%] yards [%]

pasture [%]

Dairy cows 7.3 26.5 48.4 9.1 5.0 3.7 Suckling cows 3.0 15.9 25.7 31.0 6.5 18.7 Cattle < 1 year 0.0 0.0 21.6 70.4 1.8 6.2 Breeding heifers 1–2 years

3.6 19.9 38.0 28.9 5.6 4.0


3.7 14.0 49.4 28.8 0.7 3.4


4.5 24.7 36.9 23.9 2.6 7.4


-- -- 82.3 16.7 1.0 --

Fattening pigs -- -- 91.2 8.0 0.8 --

For 2018 the same shares as for 2017 have been used.

Trends in manure management of cattle The time series shows that tied systems and systems with straw-litter decrease, whereas loose housing systems and slurry-based systems increase. In 2017, slurry-based loose housing sys-tems are predominantly used in Austria’s cattle husbandry.

While the share of pasture increased for suckling cows (and to a lesser extent also for fattening heifers and cattle < 1 year), it decreased for the other cattle categories.

Trends in manure management of swine The time series shows that housings with straw-litter for young and fattening pigs decreased and those with slatted floors increased. According to the TIHALO II study (PÖLLINGER et al. 2018), straw-litter systems decreased in 2017 compared to 2005.

In general, small farms more frequently use systems with solid manure; large farms make more use of slurry systems.

Free range systems for pigs are uncommon in Austria. Data collected within (AMON et al. 2007) and (PÖLLINGER et al. 2018) showed that hardly any pig had free access to a pasture.

N-input from straw as bedding material – cattle and swine

There is hardly any straw production in Austrian alpine grassland regions, which contribute to the production of a major proportion of Austrian milk. The import of straw from arable land re-gions is connected with remarkable costs (for collecting, pressing and transport) and that results in significantly reduced straw inputs into alpine litter-based systems compared to farms in the lowlands producing their own straw. As a consequence, overall N input from straw to manure management systems is comparatively low. Austrian assumptions for cattle are based on expert judgement of (DIETER KREUZHUBER 2013), who is ÖKL’s130 person responsible for agricultural buildings, including ÖKL recommendations for the adding of straw in manure management sys-tems.

130 Österreichisches Kuratorium für Landtechnik und Landentwicklung



Information on N inputs from straw for breeding sows, fattening pigs, goats, sheep, soliped and other animals (furred game) is taken from EMEP/EEA-Guidebook 2019, Table 3.7, as for these animal categories in Austria hardly any information is available from expert estimates or national literature. For poultry, straw inputs are calculated according to Germany’s National Inventory Report 2013 (FEDERAL ENVIRONMENT AGENCY GERMANY 2013). The following tables include the straw use per animal, day and year.

Table 260: Straw supply for cattle (per head).

kg straw per animal and day and year

tied system with solid storage

tied system with liquid slurry

loose house sys-tems with solid

manure

loose house systems with liquid slurry

kg straw

per day

kg straw per year

kg straw

kg straw per year

kg straw

kg straw per year

kg straw

kg straw

per year

Dairy cattle and suckling cows 1.5 547.5

0.2 73 4.0* / 2.5*

1 460 /

912.5

0.5 182.5

Young cattle 1.2 438 0.3 109.5

* 4 kg straw for deep litter systems and 2.5 kg straw for the bedding in solid manure systems

Table 261: Straw supply for swine, sheep, goats, horses and poultry (per head)

kg straw per animal and year Solid storage Liquid slurry (grazing)

kg straw kg straw

Fattening pigs 200 0

Breeding sows plus litter 600 0

Sheep, goats and ‘other animals’ 20 0

Horses etc. 500 0

Layers 0.5 0

Broilers 1.4 0

Turkeys 10.3 0

Other poultry (e.g. ducks) 19.5 0

In pastures and yards no straw is used. For the calculation of the N amounts the EMEP/EEA default N content of straw (0.004 kg N per kg straw) was used for all animal categories (EMEP/EEA Guidebook 2019, Table 3.7).

Manure storage – cattle and swine

Table 251 describes the share of composted and not composted solid manure for the years 1990, 2005 and 2017. The values for 2005 are taken from the TIHALO I survey (AMON et al. 2007), those for 2017 from the TIHALO II survey (PÖLLINGER et al. 2018). Data for 1990 were estimated by the Austrian expert Alfred Pöllinger in June 2008 on the basis of TIHALO I results (AMON & HÖRTENHUBER 2008). The values from 2006–2016 were derived by linear extrapolation.



Table 262: Share of composted and untreated solid manure for cattle and swine in Austria in 1990, 2005 and 2017.

1990 2005 2017 Composted

solid manure [%]

Untreated solid

manure [%]

Composted solid manure

[%]

Untreated solid

manure [%]

Composted solid

manure [%]

Untreated solid

manure [%]

Dairy cows 6.0 94.1 11.9 88.1 6.0 94.0

Suckling cows 5.9 94.2 11.7 88.3 7.0 93.0

Cattle < 1 year 5.9 94.1 11.8 88.2 6.6 93.4


5.9 94.1 11.8 88.2 6.0 94.0


4.4 95.6 8.8 91.2 6.1 93.9

Cattle > 2 years 5.7 94.3 11.4 88.6 5.4 94.6


6.4 93.7 12.7 87.3 5.2 94.8

Fattening pigs 4.2 95.8 8.4 91.6 7.4 92.6


Table 263: Slurry storage and treatment for cattle and swine in 1990, 2005 and 2017.

Dairy cows

Suckling cows

Cattle < 1 year

Breeding heifers

1–2 years

Fattening heifers, bulls

& oxen, 1–2 years

(Other) cattle

> 2 years

Breeding Sows plus

litter

(Young &) Fattening

Pigs

1990

Solid cover 73.4 76.8 78.2 74.9 79.5 78.2 83.9 74.5

Uncovered and not aerated

14.1 12.2 10.3 15.9 11.3 9.4 10.8 16.3

Uncovered and aerated

5.7 5.8 6.8 4.2 4.1 8.2 2.6 1.9

Straw cover 0 0 0 0.1 0 0.1 0.3 0.4

Plastic foil 0 0 0 0 0 0 0.1 0.4

Natural crust 6.9 5.2 4.8 5.0 5.1 4.2 2.4 6.5

2005

Solid cover 70.5 73.9 74.8 72.8 77.5 74.1 82.6 73.6


11.2 9.3 6.9 13.8 9.3 5.3 9.5 15.4


11.4 11.5 13.5 8.3 8.2 16.3 5.1 3.7

Straw cover 0 0 0 0.1 0 0.1 0.3 0.4

Plastic foil 0 0 0 0 0 0 0.1 0.4

Natural crust 6.9 5.2 4.8 5.0 5.1 4.2 2.4 6.5



Dairy cows

Suckling cows

Cattle < 1 year

Breeding heifers

1–2 years

Fattening heifers, bulls

& oxen, 1–2 years

(Other) cattle

> 2 years

Breeding Sows plus

litter

(Young &) Fattening

Pigs

2017

Solid cover 71.0 83.0 73.0 72.0 73.0 72.0 75.0 70.0


9.9 5.5 9.4 9.6 10.2 6.7 9.9 14.1


1.2 0.7 1.2 1.2 1.3 0.8 0.9 1.2

Straw cover 1.0 0 0.5 1.0 0 1.0 1.0 1.0

Plastic foil 0 0 0 0 0.1 0 2.0 2.0

Natural crust 16.9 10.8 15.9 16.2 15.4 19.5 11.2 11.7

Note: 2017 data are based on the TIHALO II survey results (PÖLLINGER et al. 2018). Data for 2005 are based on the outcomes of the TIHALO I study (AMON et al. 2007). 1990 data are based on (KONRAD 1995), TIHALO I & II study results and expert judgement (PÖLLINGER 2008), carried out in (AMON & HÖRTENHUBER 2019).


5.3.2.2 Animal excretion – cattle and swine

N excretion

N excretion values as shown in Table 253 and Table 254 are based on the following literature: (GRUBER & PÖTSCH 2006, PÖTSCH et al. 2005, STEINWIDDER & GUGGENBERGER 2003, UNTERARBEITSGRUPPE N-ADHOC 2004 and ZAR 2004) and Richtlinien Sachgerechter Düngung (BMLFUW 2017).

Table 264: Austria specific N excretion values of dairy cows for the period 1990–2018.

Year Milk yield [kg yr-1]

Nitrogen excretion [kg/animal*yr]

Year Milk yield [kg yr-1]

Nitrogen excretion [kg/animal*yr]

1990 3 791 76.62 2005 5 783 94.55

1991 3 848 77.13 2006 5 903 95.63

1992 3 908 77.67 2007 5 997 96.48

1993 3 997 78.48 2008 6 059 97.03

1994 4 076 79.18 2009 6 068 97.11

1995 4 619 84.07 2010 6 100 97.40

1996 4 670 84.53 2011 6 227 98.54

1997 4 787 85.58 2012 6 418 100.26

1998 4 924 86.82 2013 6 460 100.64

1999 5 062 88.06 2014 6 542 101.38

2000 5 210 89.39 2015 6 579 101.71

2001 5 394 91.04 2016 6 759 103.33

2002 5 487 91.89 2017 6 865 104.29

2003 5 638 93.24 2018 7 104 106.44

2004 5 802 94.72 1) From 1995 onwards data have been revised by Statistik Austria, which led to significant higher milk yield data of

Austrian dairy cows.



The Austrian N excretion data were calculated following the guidelines of the European Com-mission according to the requirements of the European nitrate directive:

Cattle: Feed rations represent data of commercial farms consulting representatives of the work-ing groups “Dairy production”. These groups are managed by well-trained advisors. Their mem-bers, i.e. farmers, regularly exchange their knowledge and experience. Forage quality is based on field studies, carried out in representative grassland and dairy farm areas. The calculations depend on feeding ration, gain of weight, nitrogen and energy uptake, efficiency, duration of livestock keeping etc. On the basis of a national study (HÄUSLER 2009) for suckling cows an av-erage milk yield of 3 500kg has been assumed for the years from 2004 onwards.

Table 265: Austria specific N excretion values of other cattle and swine.

Livestock category Nitrogen excretion [kg/animal*yr]

Suckling cows1) (1990) 69.5 Suckling cows2) (2018) 74.0 Cattle 1–2 years 53.6 Cattle < 1 year 25.7 Cattle > 2 years 68.4 Breeding sows (1990) 29.1 Breeding sows (2018) 27.7 Young & fattening pigs (1990) 9.0 Young & fattening pigs (2018) 8.8

1) Annual milk yield: 3 000 kg 2) Annual milk yield: 3 500 kg

Pigs: breeding pigs, piglets, boars, fattening pigs: number and weight of piglets, daily gain of weight, energy content of feeding, energy and nitrogen uptake, share of animals with N-reduced feeding (PÖLLINGER et al. 2018).

TAN content in excreta – cattle and swine

The mass-flow approach makes use of the total ammoniacal nitrogen (TAN) when calculating emissions. The initial share of TAN must be known as well as any transformation rates between organic N and TAN. TAN content for Austrian cattle and pig manure is given in SCHECHTNER (1991) and BMLFUW (2017).

Table 266: TAN content for Austrian cattle and pig manure after SCHECHTNER (1991) and BMLFUW (2017).

TAN content [kg NH4-N per kg Nex] Cattle – farmyard manure 0.15 Cattle – liquid manure 0.50 Swine – farmyard manure 0.15 Swine – liquid manure 0.65



5.3.2.3 Calculation of NH3 emissions – cattle and swine

NH3 emissions from cattle and swine were calculated using a country specific methodology fol-lowing the N-flow model.

Emissions of Ammonia (NH3) occur during animal housing, the storage of manure and the ap-plication of organic fertilizers on agricultural soils. Emissions of nitric oxide (NOx) were calculat-ed for manure management and field spreading of manure.

Following the revised CLRTAP Reporting Guidelines, NH3 and NOx-Emissions from the applica-tion of livestock manures to land have to be reported under 3.D Agricultural soils (3.D.a.2.a An-imal manure applied to soils). In line with the new NFR reporting, the methodological description is provided in chapter 3.D of this report.

NH3 emissions from category 3.B.1 Cattle and 3.B.3 Swine are calculated as follows:

NH3 (3.B) = NH3 (housing) + NH3 (storage)

Where no national emission factors are available, emission factors are taken from the Swiss ammonia inventory which is calculated with the computer based programme “DYNAMO” (MENZI et al. 2003, REIDY et al. 2007, REIDY & MENZI 2005). Due to similar management strategies and geographic structures, Swiss animal husbandry is closest to Austrian animal husbandry.

NH3 emissions from housing – cattle and swine

Table 256 provides NH3 emission factors for the housings of cattle and swine (EIDGENÖSSISCHE FORSCHUNGSANSTALT 1997 and DÖHLER et al. 2002).

Table 267: Emission factors for NH3 emissions from animal housing.

Manure management system Emission factor [kg NH3-N (kg N excreted)-1]

Pasture/range/paddock – cattle 0.050

Cattle, tied systems, liquid slurry system 0.040

Cattle, tied systems, solid storage system 0.039

Cattle, loose houses, liquid slurry system 0.118

Cattle, loose houses, solid storage system 0.118

Fattening pigs, liquid slurry system 0.150

Fattening pigs, solid storage system 15% of total N + 30% of the remaining TAN

Sows plus litter, liquid slurry system 0.167

Sows plus litter, solid storage system 0.167

For yards the default Tier 2 EFs from the EMEP/EEA GB 2019 have been applied (Table 3.9).

Table 268: NH3 emission factors for yards.

Manure management system Emission factor [kg NH3-N (kg TAN)-1]

Dairy cattle 0.30

Non-dairy cattle 0.53

Note: EFs are given as a proportion of TAN



N excretion per manure management system Country-specific N excretion per animal waste management system for Austrian cattle and swine has been calculated using the following formula:

Nex(MMS) = ∑ (T) [N(T) x Nex(T) x MMS(T)]

Nex(MMS) = N excretion per manure management system [kg yr-1] N(T) = number of animals of type T in the country (see Table 243, Table 244 and Table 245) Nex(T) = N excretion of animals of type T in the country [kg N animal-1 yr-1] (see Table 253, Table 254 and

Table 262) MMS(T) = fraction of Nex(T) that is managed in one of the different distinguished manure management systems

for animals of type T in the country (T) = type of animal category

Abatement factors for housing systems of cattle and swine

In submission 2019 the grooved floor system for cattle and the partly slatted floor systems for swine was implemented to the Austrian ammonia inventory (AMON & HÖRTENHUBER 2019).

Specific abatement factors from the UNECE Framework Code for Good Agricultural Practice for Reducing Ammonia Emissions (UNECE 2015) were used. The AF is multiplied with the EF.

Table 269: Abatement factors (AF) for NH3 emissions from housing systems (liquid systems cattle and swine)

Livestock category Housing system Share in liquid systems* 2017

AF

Cattle Dairy cattle

Grooved floor

8.1%

0.75

Suckling cows 3.4%

Cattle < 1 year 2.0%

Breeding heifers 1–2 years 2.2%

Fattening heifers, bulls & oxen, 1–2 years 2.8%

Cattle > 2 years 1.1%

Swine Breeding sows plus litter Partly slatted floor

47.0% 0.85

Fattening pigs 9.0%

* for cattle: share in liquid loose housing systems


NH3 emissions from manure storage – cattle and swine

NH3 emissions from storage are estimated from the amount of N left in the manure when the manure enters the storage. This amount of N is calculated as following:

From total N excretion the N excreted during grazing and the NH3-N losses from housing (see above) are subtracted. The remaining N enters the store.

Solid manure According to the EMEP/EEA GB 2019 account must also be taken of the fraction (fimm) of TAN that is immobilized in organic matter when manure is managed as solid. The default value of 0.0067 kg N kg-1 straw for fimm has been applied (EEA 2019).



Liquid manure For slurries, a fraction (fmin) of the organic N is mineralized to TAN before the gaseous emis-sions are calculated according to the EMEP/EEA GB 2019. The default value of 0.1 for fmin has been applied (EEA 2019). NH3 emission factors – cattle and swine

Table 259 provides NH3 emission factors for the storage of cattle and swine manures (EIDGENÖSSISCHE FORSCHUNGSANSTALT 1997).

Table 270: NH3 emission factors for manure storage.

Manure storage system Emission factor [kg NH3-N (kg TAN)-1]

Cattle, liquid slurry system 0.15

Cattle, solid storage system 0.30

Pigs, liquid slurry system 0.12

Pigs, solid storage system 0.30 Abatement factors for storage systems of cattle and swine manures

Table 260 shows abatement factors (AF) to emission factors (EF) for a range of manure treat-ment options. Untreated variants systems, for example uncomposted solid manure, give the reference value ‘1’. EF for other treatment options, managements and systems get an associat-ed AF, e.g. +20% for the composting of solid manure (AF = 1.2). The AF is multiplied with the EF. Factors were taken from the Swiss ammonia inventory which is calculated with the comput-er based programme ‘DYNAMO’ (MENZI et al. 2003, REIDY et al. 2007, REIDY & MENZI 2005). Due to similar management strategies and geographic structures, Swiss animal husbandry is closest to Austrian animal husbandry.

DYNAMO is based on the N flow model and estimates ammonia emissions for each stage of the manure management continuum. Animal categories, manure management systems and a range of additional parameters are considered within DYNAMO. DYNAMO parameters were adapted to Austrian specific conditions. The DYNAMO model is peer reviewed by the EAGER131 group and published in (REIDY et al. 2008, 2009).

Table 271: Abatement factors (AF) for NH3 emissions from manure storage.

Manure storage [AF]

Uncomposted solid manure 1

Composted solid manure 1.2

Uncovered tank 1

Solid cover – liquid system 0.2

Aerated open tank – liquid system 1.1

Straw cover – liquid system 0.6

Plastic foil cover – liquid system 0.4

Natural crust – liquid system 0.6

Abatement factors are fully consistent with those provided in the UNECE Framework Code for Good Agricultural Practice for Reducing Ammonia Emissions (UNECE 2015). 131 European Agricultural Gaseous Emissions Inventory Researchers Network (EAGER)



5.3.3 NH3 emissions from sheep (3.B.2), goats (3.B.4.d), horses (3.B.4.e), poultry (3.B.4.g) and other animals (3.B.4.h)

Key Category: No

For the livestock categories sheep (3.B.2), goats (3.B.4.d), horses (3.B.4.e), poultry (3.B.4.g) and other animals (3.B.4.h) the EMEP/EEA Tier 2 methodology has been applied. Tier 2 uses a mass flow approach based on the concept of TAN (EEA 2019).

5.3.3.1 Agricultural practice – non-key livestock categories

Solid systems and pasture are the relevant MMS for these animal categories in Austria.

Table 272: Share of N in animal waste management systems (non-key livestock).

Livestock category Liquid/Slurry Solid Storage Pasture/Range/Paddock

[%] [%] [%]

Sheep 0.0 65.0 35.0

Goats 0.0 94.4 5.6

Horses 0.0 80.0 20.0

Laying hens 0.0 96.0 4.0

Broilers 0.0 99.8 0.2

Turkeys 0.0 99.8 0.2

Other poultry 0.0 99.8 0.2

Other animals 0.0 20.0 80.0

Shares are kept constant for all years.

N-input from straw as bedding material – non-key livestock categories

Information on N inputs from straw for sheep, goats, soliped and other animals (furred game) is taken from the EMEP/EEA-Guidebook 2019, Table 3.7, as for these animal categories in Aus-tria hardly any information is available from expert estimates or national literature. For poultry, straw inputs are calculated according to Germany’s National Inventory Report 2013 (FEDERAL ENVIRONMENT AGENCY GERMANY 2013). The straw use per animal and year is presented in Ta-ble 250.



5.3.3.2 Animal excretion – non-key livestock categories

Country specific N excretion values are presented in the following table:

Table 273: Austria specific N excretion values of non-key livestock categories.

Livestock category Nitrogen excretion [kg/animal*yr]

Sheep 13.1

Goats 12.3

Horses 47.9

Layers 0.73

Broilers 0.28

Turkeys 1.18

Other poultry 0.48

Other animals/furred game1) 13.1 1) N-ex value of sheep applied

5.3.3.3 Calculation of NH3 emissions – non-key livestock categories

Table 263 presents the default EMEP/EEA Tier 2 NH3-N emission factors and associated pa-rameters used in the calculations for Austria’s non-key livestock categories (EEA 2019, Table 3.9).

Table 274: Default Tier 2 NH3-N EF and associated parameters for the Tier 2 methodology.

NFR Livestock category proportion of TAN

EF housing EF storage EF spreading

3.B.2 Sheep 0.50 0.22 0.32 0.90

3.B.4.d Goats 0.50 0.22 0.28 0.90

3.B.4.e Horses (mules, asses)

0.60 0.22 0.35 0.90

3.B.4.g.i Laying hens 0.70 0.20 0.08 0.45

3.B.4.g.ii Broilers 0.70 0.21 0.30 0.38

3.B.4.g.iii Turkeys 0.70 0.35 0.24 0.54

3.B.4.g.iv Other poultry 0.70 0.41(*) 0.20(*) 0.49(*)

3.B.4.h Other animals(**) 0.50 0.22 0.32 0.90 *) EF = weighted mean of ducks & geese for 2018 **) In Austria furred game, mainly deer, dominates the livestock category ‘other animals’. As sheep is the most similar

livestock category to deer, for ‘other animals’ the NH3 emission factors of sheep have been used.

NH3 emissions from housing – non-key livestock categories

NH3-N emissions from the housing of non-key animals are calculated by using the following formula:

Nex(MMS) * TAN proportion * EFhousing

Nex(MMS)= N excretion per manure management system [kg yr-1]



As indicated in Table 261, the non-key livestock categories are all managed on solid systems.

NH3 emissions from storage – non-key livestock categories

NH3-N emissions from storage are estimated from the amount of N left in the manure when it enters the storage (N left for storage).

In the calculations of emissions from the storage of animal manure the NH3-N losses from hous-ing and the fraction of TAN that is immobilized in organic matter (fimm) when manure is managed as solid are taken into account. For fimm the EMEP/EEA default value of 0.0067 has been ap-plied (EEA 2019).

Abatement factors for storage systems of layers and broilers

In submission 2019 for layers and broilers the management system “manure belt with covered storage” was implemented in Austria´s ammonia inventory (AMON & HÖRTENHUBER 2019) using specific abatement factors (AF) from the UNECE Framework Code for Good Agricultural Prac-tice for Reducing Ammonia Emissions (UNECE 2015). These abatement factors, adjusted to Austria’s agriculture practice, were multiplied with the EF.

Table 275: Abatement factors (AF) for NH3 emissions from storage systems (layers and broilers)

Livestock category

Housing system Share in solid systems 2017

AF (UNECE 2015)

AF applied in Austria

Layers systems with manure belt and covered storage

27.7% 0.3 0.58*

Broilers systems with manure belt and covered storage

28.5% 0.3 0.65**

* reduced abatement potential compared to (UNECE 2015)

** half of the abatement potential provided in (UNECE 2015) Layers: 20% of the systems with manure belts and covered storage are drying the manure on the belts through forced ventilation (PÖLLINGER et al. 2018). For these 20% the abatement po-tential of -70% (AF = 0.3) from (UNECE 2015) has been taken. For the remaining 80% of manure collected on manure belts only the half of the potential outlined in (UNECE 2015) has been ap-plied.

Broilers: no information on the drying is available. Thus, only half of the abatement potential from (UNECE 2015) has been used.

In 1990 the manure drying through forced ventilation on manure on belts was not common in Austria (PÖLLINGER 2018, carried out in AMON & HÖRTENHUBER 2019).

5.3.4 NH3 emissions from biogas plants

In previous submission NH3 emissions from anaerobic digestion at biogas facilities (reported under NFR 5.B.2, sector 5 Waste) have been included in the Austrian inventory for the first time. Emissions are calculated in sector 3 Agriculture but reported under sector 5 Waste, in line with the CLRTAP reporting Guidelines.



Activity data

Basis for estimating NH3-N losses and NH3 emissions from digesters reported under waste sec-tor (see Table 265) is the N in the manure when entering the biogas facilities, taking into ac-count all N-losses during animal housing before. The remaining N (after subtraction of NH3-N losses during the digestion process) is included in the N amount applied to soils (N left for spreading, reported in agriculture sub-sector 3.D).

Table 276: N amounts digested in biogas facilities

Year N (manure-inputs) N (vegetable-inputs) Total N inputs

[kg year-1]

1990 35 459 228 362 263 822

1991 48 191 309 630 357 821

1992 53 579 342 881 396 460

1993 71 846 456 489 528 335

1994 204 387 1 292 892 1 497 279

1995 234 264 1 486 580 1 720 844

1996 257 880 1 629 485 1 887 365

1997 328 751 2 073 984 2 402 735

1998 387 594 2 439 826 2 827 420

1999 529 961 3 336 562 3 866 523

2000 631 000 3 933 677 4 564 676

2001 721 658 4 489 945 5 211 603

2002 805 505 4 991 742 5 797 247

2003 867 011 5 382 074 6 249 085

2004 930 939 5 761 510 6 692 449

2005 985 590 6 066 373 7 051 963

2006 1 036 171 6 342 572 7 378 743

2007 1 152 085 6 988 645 8 140 729

2008 1 204 268 8 227 318 9 431 586

2009 1 251 848 9 745 371 10 997 219

2010 1 299 139 9 163 634 10 462 772

2011 1 356 376 8 718 846 10 075 222

2012 1 429 683 9 145 218 10 574 901

2013 1 498 654 9 537 291 11 035 945

2014 1 534 185 9 715 635 11 249 820

2015 1 613 356 10 190 403 11 803 759

2016 1 557 739 8 559 247 10 116 986

2017 1 281 549 9 326 988 10 608 538

2018 1 284 870 9 360 074 10 644 944



Methodology

The calculations were done according to the Tier 1 methodology of the EMEP/EEA Guidebook 2019 (EEA 2019, Chapter 5.B.2, Table 3.1).

5.3.5 NOx emissions from Manure Management (3.B)

Key Category: No

NOx emissions from manure management were calculated according to the Tier 2 methodology as outlined in the EMEP/EEA Guidebook 2019 (EEA 2019). The calculations make use of the mass-flow approach based on the concept of a flow of TAN through the manure management system.

Activity data and methodology

According to the EMEP/EEA GB 2019, NOx emissions occur from slurry stores based on the amount of TAN. These N amounts per type of manure system have been already estimated within NH3 calculations (please refer to chapter 5.3.2.3 for cattle and swine and to chapter 5.3.3.3 for the other livestock categories) and are multiplied with an emission factor (slurry or solid).

For cattle and swine national TAN contents are available from (SCHECHTNER 1991) (see Table 255). Default TAN values according to the EMEP/EEA GB 2019, Table 3.9, have been applied for sheep, goats, horses, poultry and deer. Emission factors

Emission factors are taken from the EMEP/EEA GB 2019, Table 3.10. The NO emission factors for slurry and solid (storage) are expressed as proportion of TAN (0.0001 for slurry and 0.01 for solid).

5.3.6 N2 emissions from manure management

From submission 2019 onwards N2 losses have been included in the Austrian N flow model (AMON & HÖRTENHUBER 2019).

Activity data and methodology

N2 emissions result from storage of manure and need to be taken into account in the mass-flow calculation according to the EMEP/EEA GB 2019. N2 emission calculations are based on the amounts of TAN left for storage per type of manure system (see also NOx calculations, chapter 5.3.5). These amounts of N are multiplied with the respective EF (slurry or solid).

National TAN contents for cattle and swine are taken from (SCHECHTNER 1991, presented in Ta-ble 255). For the other livestock categories the default values according to the EMEP/EEA GB 2019, Table 3.9, are used.



Emission factors For both slurry and litter-based manures, the default N2 emission factors from Table 3.10 (EEA 2019) have been applied.

5.3.7 NMVOC from Manure Management (3.B)

Key Category: Cattle (3.B.1)

Austria uses the Tier 2 methodology as recommended in the NEC Review 2018 (EC 2018).

Activity data

Livestock data Livestock numbers were taken from the Austrian official statistics (STATISTIK AUSTRIA 2019b) (please refer to Table 243, Table 244 and Table 245). Following a recommendation under the NEC Review 2018 (EC 2018), Austria splitted the piglets numbers < 20 kg into suckling piglets < 8 kg and weaned piglets 8–20 kg based on expert judgement (STATISTIK AUSTRIA 2018d). This approach was accepted by the NEC Review 2018 and applied for all inventory years. Emission estimates have been updated accordingly by taking into account swine numbers between 8 and 20 kg in the total number of fattening pigs.

Manure management system data (MMS) Information on MMS distributions used in sector manure management were taken from (KONRAD 1995), (AMON et al. 2007) and (PÖLLINGER et al. 2018).

Silage feeding Currently, less information on silage feeding is available in Austria. Therefore, the maximum proportion of silage in dry matter of approximately 50 % of the total dry matter intake has been applied for dairy cattle, as provided in the EMEP/EEA GB 2019. For the other cattle categories the proportion of silage in dry matter has been estimated based on animal diets worked out by nutrition experts as included in (AMON et al. 2002).

Sheep, goats and horses are not fed with silage in Austria.

Methodology

The Tier 2 methodology according to the EMEP/EEA GB 2019 (EEA 2019) has been applied for all livestock categories. As a consequence of the Tier 2 calculations, NMVOC emissions are split into emissions from buildings (feeding, housing and storage), application (reported under NFR category 3.D.a.2.a) and grazing (reported under NFR 3.D.a.3).

Cattle

The Tier 2 approach based on the feed intake in MJ was used. For detailed information on na-tional feed intake data for cattle please refer to chapter 5 of “Austria’s National Inventory Report 2020 – Submission under the United Nations Framework Convention on Climate Change and the Kyoto Protocol” (UMWELTBUNDESAMT 2020a).

Calculations have been done on the basis of feed intake and silage fraction according to the formulas as provided in the EMEP/EEA GB 2019, p. 29. Default Tier 2 emission factors for feed-ing, building and grazing are taken from Table 3.11 of the EMEP/EEA GB 2019. Table 266 pro-vides the resulting country-specific emission factors for the different cattle categories for 2018.



Table 277: Country-specific NMVOC emission factors of cattle for 2018.

Livestock cate-gory

3.B 3.B 3.D.a.2.a 3.D.a.3

EF silage feeding [kg NMVOC head-

1 yr-1]

EF housing incl. storag

[kg NMVOC head-1 yr-1]

EF application [kg NMVOC head-

1 yr-1]

EF grazing [kg NMVOC head-

1 yr-1]

Dairy cows 14.00 5.47 7.25 0.03

Suckling cows 5.46 3.46 3.45 0.11

Cattle < 1 year 8.14 2.50 1.71 0.03


8.54 2.78 2.95 0.02


7.78 2.44 2.63 0.01

Cattle > 2 years 5.24 2.45 2.68 0.03

All livestock categories other than cattle

NMVOC emissions from swine, sheep, goats, horses, poultry and deer were calculated using the EMEP/EEA 2019 Tier 2 methodology on the basis of VS excretion (EEA 2019, p. 30). For detailed information on the VS excretion, please refer to chapter 5 of “Austria’s National Inven-tory Report 2020 – Submission under the United Nations Framework Convention on Climate Change and the Kyoto Protocol” (UMWELTBUNDESAMT 2020a).

For the calculation of NMVOC emissions from housing and grazing the default NMVOC Tier 2 emission factors have been applied (Table 3.12 of the EMEP/EEA GB 2019). Table 267 pro-vides an overview of NMVOC emission factors and parameters used in the calculations.

Table 278: NMVOC emission factors and fractions used for livestock categories other than cattle for 2017

Livestock category

3.B Housing 3.B Manure store 3.D.a.2.a Applica-tion

3.D.a.3 Grazing

kg NMVOC / kg VS ex

NH3_storage / NH3_building

NH3 application / NH3 building

kg NMVOC / kg VS ex

Breeding sows 0.007042 0.16 0.44 -

Young & fatten-ing pigs

0.001703 0.17 0.46 -

Sheep 0.001614 1.13 2.26 0.00002349

Goats 0.001614 1.13 2.09 0.00002349

Horses 0.001614 1.37 1.82 0.00002349

Laying hens 0.005684 0.20 0.44 -

Broilers 0.009147 0.40 0.99 -

Turkeys 0.005684 0.51 0.38 -

Other poultry 0.005684 0.39 0.57 -

Other animals 0.001614 1.13 2.19 0.00002349

Livestock other than cattle is not fed with silage in Austria.




Update of activity data

Animal livestock Livestock numbers of poultry and other animals (mainly deer) have been revised as new data has become available based on the final results of the farm structure survey 2016 (STATISTIK AUSTRIA 1990–2019). To avoid jumps in the time series, the years 2014 and 2015 have been in-terpolated. As currently no updated data is available for the respective livestock categories, the values of 2016 have been used for the years 2017 and 2018.

Manure Management (3.B) – NH3

The main reason for revised NH3 emissions from manure management is the implementation of the new EMEP/EEA Guidebook 2019 in Austria’s air emission inventory. The 2019 version of the Guidebook provides updated NH3 emission factors for housing and storage for the livestock categories layers, broilers, sheep and other animals. Furthermore, the calculation method, which is based on the fraction of TAN that is immobilised in organic matter (fimm) when the ma-nure is managed as a litter-based solid and the litter is straw, has been revised. According to (EEA 2019), this immobilisation greatly reduces the potential NH3-N emission during storage and after application.

The improved calculations resulted in lower NH3 emissions from manure management for the whole time series (– 1.4 kt NH3 in 2017)

Biological treatment of waste (5.B.2) – NH3

NH3 emissions from anaerobic digestion at biogas facilities are calculated in sector 3 Agriculture but reported under sector 5 Waste. The Tier 1 methodology of the EMEP/EEA Guidebook is applied. In the EMEP/EEA GB 2019 the NH3-N EF was changed from 0.0286 kg of NH3-N to 0.0275 kg of NH3-N, leading to a downward revision across the whole time series (– 0.02 kt NH3 in 2017).

Manure Management (3.B) – NOx

NOx emissions are calculated using a mass-flow approach based on the concept of a flow of TAN through the manure management system according to the EMEP/EEA GB 2019. Although there were no changes in the methodology for NOx between the Guidebook versions 2016 and 2019, the revisions in the ammonia inventory had an impact on NOx and resulted in lower emis-sions for the whole time series (– 0.01 kt NOx in 2017).

Manure Management (3.B) – NMVOC

The NMVOC emission calculations according to the 2019 EMEP/EEA Tier 2 methodology are strongly linked to the compilation of the ammonia emissions inventory. Therefore, although there were no changes in the methodology for NMVOC between the Guidebook versions 2016 and 2019, the revisions to the ammonia inventory also had an impact on NMVOC emissions. The improved calculations resulted in recalculations for the whole time series (+ 0.09 kt NMVOC in 2017).



5.4 NFR 3.B Particle Emissions from Manure Management

Key Category: No

In NRF category 3.B Manure Management particle emissions from Animal Husbandry are in-cluded.


Particle emissions from animal husbandry are primary connected with the manipulation of for-age, a smaller part arises from dispersed excrements and litter. Wet vegetation and mineral par-ticles of soils are assumed to be negligible, thus particle emissions from free-range animals are not included.

The estimations of particle emissions from animal husbandry are related to the Austrian live-stock number. Activity data

The Austrian official statistics (STATISTIK AUSTRIA 2019b) provides national data of annual live-stock numbers on a very detailed level (please refer to Table 243, Table 244 and Table 245).

Emission Factors

Measurements and emission estimates of ’primary biological aerosol particles’ based on meas-urements (WINIWARTER et al. 2009) don’t indicate high amounts of cellulosic materials existing in the atmosphere. According to WINIWARTER et al. (2009), the default EMEP/EEA EFs seem to significantly overestimate emissions and should be better indicated as 'potential emissions' be-cause resulting high emission values could not be validated by measurements. One reason is that underlying measurement data used for generation of default EFs (e.g. TAKAI et al., 1998) is based on indoor air measurements (with focus on 'inhalable dust' and 'respirable dust') neglect-ing the losses during transfer to the outdoor air. Following Winiwarter et al (2009) the origin of dust material which is relevant for this source category is mainly fodder, bedding material and excrements and they tend to agglomerate under humid weather conditions.

Based on these results and due to lack of more reliable up-to-date data the emission factors of the RAINS model (LÜKEWILLE et al. 2001) have been assessed to be much more accurate for Austria. Calculations result in lower and much more realistic estimates compared to the results when using the EMEP/EEA GB 2019 default Tier 1 emission factors.

In Table 268 the applied emission factors are listed.

Table 279: TSP emission factors animal housing.

Livestock Emission Factor [kg TSP/animal]

Livestock Emission Factor [kg TSP/animal]

Dairy cows 0.235 Laying hens 0.016 Other cattle 0.235 Broilers 0.016 Fattening pigs 0.108 Turkeys 0.016 Sows 0.108 Other poultry 0.016 Ovines 0.235 Goats 0.153 Horses 0.153 Other animals 0.016



Following (KLIMONT et al. 2002) the share of PM10 in TSP is assumed to be 45% and the share of PM2.5 in TSP is assumed to be 10%.

It is supposed, that there is no condensable component included in the PM10 and PM2.5 emission factors (see also chapter 12.3) although it is not described explicitly in (WINIWARTER et al. 2007 and 2009) and (LÜKEWILLE et al. 2001).


Reasons for the recalculated emissions from 2014 to 2017 are the updated activity data of poul-try and other animals.

5.5 NFR 3.D Agricultural Soils

NFR sector 3.D Agricultural Soils includes emissions of ammonia (NH3), nitric oxide (NOx), NMVOC and particulate matter (TSP, PM). The methodology for estimating PM emissions is presented in a separate chapter (Chapter 5.6).


In the Austrian inventory source category 3.D Agricultural Soils comprises NH3 and NOx emis-sions from: Application of inorganic N fertilizers (3.D.a.1); Application of organic N fertilizers (3.D.a.2) including: Animal manure applied to soils (3.D.a.2.a). This emission source is reported under NFR cat-

egory 3.D Agricultural Soils in compliance with the revised CLRTAP Reporting Guidelines 2014. Up to submission 2015 NH3 emissions from this source were reported under source category 4.B Manure management.

Sewage sludge applied to soils (3.D.a.2.b) and Other organic fertilizers applied to soils (3.D.a.2.c), which comprises N inputs from digested

energy crops in biogas slurry and compost. NH3 emissions from: Urine and dung deposited by grazing animals (3.D.a.3) and NMVOC emissions from: Animal manure applied to soils (3.D.a.2.a), reported for the first time in submission 2019 as a

consequence of improved calculations in sector 3.B Manure Management (Tier 2 methodolo-gy).

Urine and dung deposited by grazing animals (3.D.a.3), reported for the first time in submis-sion 2019 as a consequence of improved calculations in sector 3.B Manure Management (Ti-er 2 methodology).

Cultivated crops (3.D.e)



5.5.2 Inorganic N-fertilizers (NFR 3.D.a.1)

Key Category: NH3

Activity Data

Austria estimates emissions from different types of mineral fertilisers according to the EMEP/EEA GB 2019. Activity data are based on Austria’s official national mineral fertilizer sta-tistics, annually compiled by Agrarmarkt Austria (AMA). National fertiliser statistics are annually published in the so-called “Green Reports” (BMNT 2000–2019).

Detailed historical data for different mineral fertiliser types are available from 1990 to 1994 (due to the fertilizer tax collected at that time). National data of urea use is available for the entire time series (Raiffeisen Ware Austria (RWA), Austria’s leading fertilizer trading firm provided data 1995–2012, Austrian Federal Ministry of Sustainability and Tourism, provided data 2013-2014). From 2015 onwards detailed data for different types of fertilisers are available. A consistent time series of fertiliser types other than urea has been generated by linear interpolation and adjust-ment to annual total mineral fertiliser amounts in consistency with Austria’s annual national sta-tistics.

Sales data are changing very rapidly due to changing market prices, high inter-annual variations are caused by the effect of storage: Not the whole amount purchased is applied in the year of purchase. The fertilizer tax intensified this effect at the beginning of the 1990ies. Considering this effect, the arithmetic average of each two years is used as fertilizer application data. Table 269 provides national N fertiliser data from 1990 to 2018.

Table 280: N usage of different types of mineral fertilizers (arithmetic average of two years) in Austria 1990–2018.

Year Calcium ammonium

nitrate (CAN)

N solutions (Urea AN)

Ammonium sulphate

(AS)

other straight N

compounds and

equivalent to calcium nitrate

Calcium nitrate (CN)

NPK mixtures

Other Urea

[t N/year]

1990 79 024 - 3 814 3 300 15 50 945 76 2 807 1991 79 434 - 3 538 3 657 18 49 083 98 3 710 1992 79 956 - 2 539 4 742 18 46 073 168 3 926 1993 76 704 - 920 6 229 16 42 419 228 3 682 1994 73 520 - 342 7 203 15 40 656 227 4 198 1995 74 114 20 400 7 535 16 40 019 208 5 058 1996 74 259 59 639 7 426 18 39 145 205 4 899 1997 76 242 98 878 7 318 19 38 271 203 5 520 1998 77 126 138 1 118 7 209 21 37 397 201 6 440 1999 71 497 177 1 357 7 101 23 36 523 198 6 624 2000 70 547 216 1 597 6 992 25 35 649 196 5 328 2001 71 791 256 1 836 6 883 27 34 775 194 3 589 2002 75 184 295 2 075 6 775 28 33 901 191 3 900 2003 62 950 334 2 315 6 666 30 33 027 189 5 488 2004 48 843 374 2 554 6 558 32 32 153 187 6 900 2005 51 614 413 2 794 6 449 34 31 279 184 7 483 2006 51 760 452 3 033 6 341 35 30 405 182 9 491



Year Calcium ammonium

nitrate (CAN)

N solutions (Urea AN)

Ammonium sulphate

(AS)

other straight N

compounds and

equivalent to calcium nitrate

Calcium nitrate (CN)

NPK mixtures

Other Urea

[t N/year]

2007 52 351 492 3 272 6 232 37 29 531 180 11 405 2008 69 276 531 3 512 6 124 39 28 657 177 10 534 2009 58 031 570 3 751 6 015 41 27 783 175 13 984 2010 38 384 610 3 991 5 907 43 26 909 172 12 450 2011 55 080 649 4 230 5 798 44 26 035 170 11 683 2012 57 214 688 4 469 5 689 46 25 161 168 13 800 2013 55 660 728 4 709 5 581 48 24 287 165 13 685 2014 60 808 767 4 948 5 472 50 23 413 163 16 189 2015 69 977 806 5 188 5 364 51 22 539 161 16 848 2016 73 583 764 5 462 5 066 67 21 276 303 19 917 2017 67 977 764 5 671 5 272 60 21 010 306 19 103 2018 67 774 910 5 792 5 177 44 20 186 334 15 203

Data sources: Annual fertilizer statistics compiled by AMA (Agrarmarkt Austria, www.ama.at) and annually published in the “Green Reports” (BMNT, www.gruenerbericht.at) Urea data 1995 to 2014: Raiffeisen Ware Austria, sales company (http://www.rwa.at) & BMNT (2013 & 2014) Fertiliser types other than urea for years 1995 to 2014: derived by linear interpolation and adjusted to total annual N amounts in consistency to annual national statistics From 2015 onwards: annual amounts per fertilizer type published by Agrarmarkt Austria (AMA 2019): www.ama.at

Emissions of ammonia (NH3)

NH3 emissions from synthetic fertilizers are estimated using a country specific methodology which requires detailed information on urea fertilizer application. The EMEP/EEA GB 2019 pro-vides specific NH3 emission factors for different types of synthetic fertilizers and for different cli-matic conditions and refers to the IPCC 2006 Guidelines regarding the definitions of climatic zones. According to IPCC 2006, Austria belongs to Group III ‘temperate and cool temperate countries’ with largely acidic soils. 65% of Austria´s soils are classified as normal (pH<7) and 35% as high (pH>=7) based on Austrian Soil Information System – BORIS – (http://www.borisdaten.at).

In Austria, full time-series data for the different mineral fertiliser types is shown in Table 269. For all these types of mineral fertilizer the weighted average of the respective default emission fac-tors for normal pH soils and high pH soils (EEA 2016, table 3.2) have been calculated. The result-ing emission factors, adjusted to Austrian conditions, are indicated in the following table.

http://www.ama.at)p/

http://www.gruenerbericht.at/

http://www.rwa.at/

http://www.ama.at/

http://www.borisdaten.at/



Table 281: NH3 emission factors for the different types of mineral fertilisers in Austria

Mineral fertiliser Emission factors (EMEP/EEA GB 2019)

Emission factors (EMEP/EEA GB 2019)

Weighted emission factors

normal (ph <=7) high (ph >7) 65% normal, 35%

high

[g NH3 (kg N applied)-1]

Calcium ammonium nitra-te (CAN)

8 17 11

N solutions (Urea AN) 98 95 97

Ammonium sulphate (AS) 90 165 116

Calcium nitrate (CN) 10 19 13

Other straight N com-pounds

10 19 13

NPK mixtures 50 91 64

Urea 155 164 158

Other - - 50(*) (*) For other fertilisers the 2016 EMEP/EEA default Tier 1 EF has been used. Abatement factor for rapid incorporation of urea

In 2019 a representative survey (‘Application of urea fertilizer in the Austrian agriculture’) inves-tigating the amount, the type (stabilized, non-stabilized) and the incorporation practice of urea was carried out (BAUMGARTEN et. al 2019). Study results show that in Austria 41% of the non-stabilized urea is incorporated at least on the same day of application. Following the UNECE Framework Code for Good Agricultural Practice for Reducing Ammonia Emissions (UNECE 2015) quickly mixing urea into the soils reduces emissions by around 50%-80%. For emission calculation in the Austrian inventory the lower boundary of 50% has been chosen. Emissions of nitric oxide (NOx) The Tier 1 methodology according to the EMEP/EEA GB 2019 is applied. Emissions of NOx are calculated as a fixed percentage of total fertilizer nitrogen applied to soil. For all mineral fertilizer types the default emission factor of 4% is used (0.04 kg NO per kg applied fertilizer-N).

5.5.3 Organic N-fertilizers applied to soils (NFR 3.D.a.2)

Key source: NH3, NOx

NFR source category 3.D.a.2 Organic fertilizers comprise emissions from Animal manure ap-plied to soils (3.D.a.2.a), Sewage sludge applied to soils (3.D.a.2.b) and Other organic fertilizers applied to soils (3.D.a.2.c) including N inputs from digested energy crops (biogas plants) and compost.

5.5.3.1 Animal manure applied to soils (NFR 3.D.a.2.a)

Emissions of ammonia (NH3), nitric oxide (NOx) and non-methane volatile organic compounds (NMVOC) occur during the application of animal manure on agricultural soils. Following the re-vised CLRTAP Reporting Guidelines, emissions are to be reported under Agricultural Soils (NFR 3.D.a.2.a Animal manure applied to soils).



Activity Data

Livestock numbers and information on MMS are described in chapter 5.3.

Nitrogen left for spreading

After housing and storage, manure is applied to agricultural soils. Manure application is con-nected with NH3-N, NOx-N and N2O-N losses that depend on the amount of manure N. With re-gard to a comprehensive treatment of the nitrogen budged, Austria established a link between the ammonia and nitrous oxide emissions inventory. A detailed description of the methods ap-plied for the calculation of N2O emissions is given in the report “Austria’s National Inventory Re-port 2020 – Submission under the United Nations Framework Convention on Climate Change and the Kyoto Protocol” (UMWELTBUNDESAMT 2020a).

From total N excretion the following losses were subtracted: N excreted during grazing NH3-N losses from the housings and yards NH3-N losses from manure storage NH3-N losses from biogas plants NOx-N losses from manure management N2O-N losses from manure management N2-losses during manure storage The remaining N is applied to agricultural soils.

NH3 emissions from animal manure applied to soils – cattle and swine

A country specific methodology has been applied.

This method distinguishes between the types of waste produced by each animal sub category: solid manure and liquid slurry. This is relevant, because TAN contents and therefore NH3 emis-sions are highly dependent on the quality of waste and organic matter content in slurry. Accord-ing to the EMEP/EEA Emission Inventory Guidebook 2019 the N input from straw use in ma-nure management systems is taken into account.

NH3 emissions from manure nitrogen applied to soils have been calculated using the following formula:

NH3-Nspread = NexLFS * (FracSS * FTAN SS * EF-NH3-N spread SS + FracLS-bc * FTAN LS * EF-NH3-N spread LS +

FracLS-bs * FTAN LS * EF-NH3-N spread LS * CFbs)

NH3-N spread = NH3-N emissions driven by intentional spreading of animal waste from Manure Management systems on agricultural soils (droppings of grazing animals are not included!)

NexLFS = Annual amount of nitrogen in animal excreta left for spreading on agricultural soils, corrected for losses during manure management; it does not include nitrogen from grazing animals

FracSS = Fraction of nitrogen left for spreading produced as farmyard manure in a solid waste management system

FracLS-bc = Fraction of nitrogen left for spreading produced as liquid slurry in a liquid waste management system (broadcast spreading)



FracLS-bs = Fraction of nitrogen left for spreading produced as liquid slurry in a liquid waste management system (band spreading)

CFbs = Correction factor band spreading FTAN SS = Fraction of total ammoniacal nitrogen (TAN) in animal waste produced in a solid waste

management system including N input from straw FTAN LS = Fraction of total ammoniacal nitrogen (TAN) in animal waste produced as slurry in a liquid

waste management system including N input from straw EF-NH3-Nspread SS = NH3-N Emission factor of animal waste from a solid manure system (farmyard manure)

spread on agricultural soils (broadcast spreading) EF-NH3-Nspread LS = NH3-N Emission factor of animal waste from a liquid slurry waste management system spread

on agricultural soils (broadcast spreading)

Application technologies – cattle and swine

Since inventory revision 2008 the agriculture inventory considers band spreading application of liquid manure. Table 271 gives information on slurry application for the years 1990, 2005 and 2017. The values for the year 1990 are expected to be the half of the ones in 2005, taken from the TIHALO I survey (expert estimation by Alfred Pöllinger, June 2008). For 2017, the data is stemming from the TIHALO II survey (PÖLLINGER et al. 2018). For 2018 the same values as for 2017 have been used.

Table 282: Cattle and pig slurry application in Austria 1990, 2005 and 2017.

Animal category: 1990 2005 2017 Broadcast application

(%)

Low-emission spreading

(%)

Broadcast application

(%)


(%)

Broadcast application

(%)


(%)

Dairy cows 96.2 3.8 92.4 7.6 94.5 5.5

Suckling cows 97.1 2.9 94.2 5.8 94.5 5.5

Cattle < 1 year 96.6 3.5 93.1 6.9 94.5 5.5


96.3 3.7 92.6 7.4 94.5 5.5


98.4 1.7 96.7 3.3 94.5 5.5

Cattle > 2 years 94.7 5.3 89.4 10.6 94.5 5.5

Breeding sows plus litter 98.0 2.1 95.9 4.1 68.0 32.0

Fattening pigs 97.0 3.0 94.0 6.0 68.0 32.0

Following the TIHALO II study (PÖLLINGER et al. 2018) the use of low-emission manure spread-ing techniques for the application of cattle slurry is still low. However, for pig slurries the share of low- emission spreading techniques has been increased significantly in 2017 compared to 2005. Trailing shoe and slurry injection are still not common techniques in Austria in 2017 (1–2% of to-tal low-emission manure spreading).



NH3 emission factors NH3 emission factors for spreading of slurry and farmyard manure (expressed as share of TAN) following (REIDY et al. 2007) have been applied:

Table 283: Emission factors for NH3 emissions from animal waste application.

Application technique Emission factor [kg NH3-N (kg TAN)-1]

spreading solid manure cattle 0.79

spreading solid manure pigs 0.81

broadcast spreading liquid manure cattle 0.50

broadcast spreading liquid manure pigs 0.25

Abatement factors for low-emission manure spreading technologies (slurry) Table 273 presents weighted abatement factors (AF) derived from average usages of several reduced-emission techniques for slurry application in 1990, 2005 and 2017. The AF is multiplied with the EF of broadcast spreading (reference value: 1). Factors were taken from the Swiss computer based programme „DYNAMO” (MENZI et al. 2003, REIDY et al. 2007, REIDY & MENZI 2005) and are fully consistent with the abatement factors provided in the UNECE Framework Code for Good Agricultural Practice for Reducing Ammonia Emissions (UNECE 2015).

Additionally to band spreaders in 2017 also trailing shoes and injectors were used (PÖLLINGER et al. 2018). Thus, the AF had to be adjusted accordingly based on the respective shares and abatement potentials provided in (UNECE 2015). For the years 2006–2016, the AF has been determined by linear interpolation. For 2018 the same values as for 2017 have been used.

Table 284: Abatement factors (AF) for NH3 emissions from slurry application.

Application technique Average weighted AF

AF (Unece 2015) 1990 2005 2017

Broadcast spreading 1 1 1 1

Low-emission manure spreading

0.70 0.70 0.65*

Band spreading 0.70

Trailing shoe 0.50

Shallow injection 0.20

*weighted average of band spreaders, trailing shoe and shallow injection

NH3 emissions from animal manure applied to soils – non-key livestock categories

For sheep, goats, horses, poultry and other animals the default EMEP/EEA Tier 2 NH3-N emis-sion factors and the default TAN values have been used (EEA 2019, Table 3.9) as also indicated in Table 263. All N-losses (NH3-N, NOx-N, N2O-N and N2 losses) at the previous stages of ma-nure (housing and storage) have been subtracted in line with the N-flow approach. As already described above, Austria established a link between the ammonia and nitrous oxide emissions inventory. In line with the EMEP/EEA Guidebook 2019 the N input from straw use in manure management systems has been taken into account.



Abatement factors for rapid incorporation

In submission 2019, rapid incorporation of animal manures (see Table 274) has been imple-mented to Austria´s ammonia inventory (AMON & HÖRTENHUBER 2019) for the first time. 1990 values have been derived by expert judgement (PÖLLINGER 2018), carried out in (AMON & HÖRTENHUBER 2019). The years in between have been derived by linear interpolation. Abate-ment factors have been taken from (UNECE 2015); the abatement factor for humid conditions (timing) before application has been taken from (REIDY & MENZI 2007). For 2018 the same val-ues as for 2017 have been used.

Table 285: Rapid incorporation practised in Austria in 2017 based on (PÖLLINGER et al. 2018) and (PÖLLINGER 2018)

Livestock category

Solid manure Liquid manure humid con-ditions (tim-ing) before application

incorporation < 4 hours

incorporation <12 hours



1:1 dilution of slurry

AF = 0.45 AF = 0.50 AF = 0.45 AF = 0.70 AF = 0.70 AF = 0.90

Cattle 22% 60% 22% 60% 3% 64-70%*

Swine 37% 59% 36% 59% 28 67-68%**

Poultry 50% 50% - - - 70%

Sheep 20% 60% - - - 60%

Goats 20% 60% - - - 60%

Horses 20% 60% - - - 60%

Other animals 20% 60% - - - 60%

Note: the values given in the table indicate the shares in total solid/liquid manure

*depending on cattle category

**depending on swine category

Only the part of manure which is applied on arable land can potentially be incorporated into soils. There is no technical potential for manure amounts applied on grassland. For cattle it is assumed that only 20% of the manure is applied on arable land (the rest is applied on grass-land), whereas for pigs, layers, broilers and turkeys the share of manure applied on arable land is 95%. 80% of duck manure, 30% of goat manure and 20% of the manure of sheep, horses and other animals is applied on arable land (PÖLLINGER 2018).

NOx Emissions from animal manure applied to soils

The Tier 1 methodology according to the EMEP/EEA GB 2019, chapter 3.D, is applied. The de-fault emission factor of 0.04 kg NO per kg of organic fertilizer-N spread on agricultural soils is used, which has been taken from table 3.1 (EEA 2019). NMVOC Emissions from animal manure applied to soils

NMVOC emissions from category 3.D.a.2.a animal manure applied to soils are calculated with the EMEP/EEA Tier 2 approach. The calculation method comprises EF for buildings (feeding, housing and storage), manure application and grazing. For further details on methodologies and parameters used please refer to sub-sector 3.B Manure management, chapter 5.3.7.



5.5.3.2 Sewage sludge applied to soils (NFR 3.D.a.2.b)

Ammonia emissions (NH3) The default emission factor of sewage sludge taken from (EEA 2019) has been applied (0.13 kg NH3/kg fertilizer N).

Emissions of nitrogen oxide (NOx) NOx emissions were estimated according to the EMEP/EEA GB 2019 (EEA 2019, Annex 2) us-ing the default Tier 1 EF of NO for sewage sludge (0.04 kg NO2/kg sewage sludge N).

Activity Data

In the frame of the reporting obligation under the Urban Wastewater Directive (91/271/EEC) the annual amount of sewage sludge as ton dry substance per year (t DS/a) is collected by the au-thorities of the Austrian Provincial Governments. After quality assessment and aggregation the data are reported once a year to the national authorities.

Table 286: Amount of sewage sludge (dry matter) produced in Austria, 1990–2018.

Year Total [t dm] agriculturally applied [t dm] agriculturally applied [%] 1990 161 936 31 507 19.5 1991 161 936 31 507 19.5 1992 200 000 30 000 15.0 1993 300 000 45 000 15.0 1994 350 000 38 500 11.0 1995 390 500 42 400 10.9 1996 390 500 42 955 11.0 1997 390 500 42 955 11.0 1998 392 909 43 220 11.0 1999 392 909 43 220 11.0 2000 392 909 43 220 11.0 2001 398 800 41 600 10.4 2002 322 096 36 065 11.2 2003 315 130 39 186 12.4 2004 294 942 35 357 12.0 2005 290 110 35 541 12.3 2006 241 364 39 369 16.3 2007 245 202 40 713 16.6 2008 248 169 39 247 15.8 2009 252 181 39 945 15.8 2010 262 805 44 354 16.9 2011 265 962 43 796 16.5 2012 266 949 41 487 15.5 2013 238 273 38 231 16.0 2014 239 044 39 626 16.6 2015 234 880 46 861 20.0 2016 237 982 48 314 20.3 2017 236 180 47 549 20.1 2018 234 481 48 170 20.5



Amounts of agriculturally applied sewage sludge were obtained from: Water Quality Report 2000 (PHILIPPITSCH et al. 2001), Report on sewage sludge (UMWELTBUNDESAMT 1997), Austrian report on water pollution control (BMLFUW 2002a) and deliveries from Austria’s federal provinces to Umweltbundesamt (UMWELTBUNDESAMT 2011, 2013, 2014a, 2015, 2016a, 2017a, 2018, 2019).

Data on N content of sewage sludge was obtained from (UMWELTBUNDESAMT 1997). The study contains sewage sludge analyses carried out by the Umweltbundesamt. Digested sludge sam-ples from 17 municipal sewage sludge treatment plants taken in winter 1994/1995 were investi-gated with regard to more than one hundred inorganic, organic and biological parameters in or-der to get an idea of the quality of municipal sewage sludge. Following this study a mean value of 3.9% N in dry matter was taken.

In 2007 the N-content value of sewage sludge was re-examined. The comparison with national Studies (ZESSNER, M. 1999) and (ÖWAV-Regelblatt Nr. 17 – Landwirtschaftliche Verwertung von Klärschlamm 2004 – www.oewav.at approved the value of 3.9% N/dm. The amount of nitrogen input from agriculturally applied sewage sludge was calculated accord-ing following formula:

FSslu = SsluN * Ssluagric

FSslu = Annual nitrogen input to soils by agriculturally applied sewage sludge [t N]

SsluN = Nitrogen content in dry matter [%] – 3.9%

Ssluagric = Annual amount of sewage sludge agriculturally applied [t/t] (see Table 275)

5.5.3.3 Other organic fertilizers applied to soils (NFR 3.D.a.2.c)

This source category includes the N inputs from energy crops applied to soils as fertilizer after the digestion process in bio-

gas plants (digestates) and the N inputs from compost applied on agricultural soils. Ammonia emissions (NH3)

The Tier 1 approach according to the EMEP/EEA Emission Inventory Guidebook 2019 is ap-plied. The default emission factor for other organic wastes of 0.08 kg NH3 per kg N applied has been used (EEA 2019, Table 3.1).

Emissions of nitric oxide (NOx)

The Tier 1 approach according to the EMEP/EEA Emission Inventory Guidebook 2019 is ap-plied. The default NO emission factor for other organic wastes of 0.04 kg NO/kg waste N ap-plied (EEA 2019, Table 3.1) has been used.

http://www.oewav.at/



Activity Data

Energy crops

The calculation of N from anaerobically digested energy crops (digestates) was done on the ba-sis of raw material and energy balances reported by E-Control (E-CONTROL 2008, 2011, 2013, 2017, 2018 & 2019). N content of digested energy crops was derived from specific literature (RESCH et al. 2006; DLG 1997; LANDESBETRIEB LANDWIRTSCHAFT HESSEN 2013). Amounts of di-gested manure N are calculated in sector manure management.

Table 287: N from biogas slurry and compost.

Year Digestates (livestock manures) [kg N year-1]

Digestates (veg. part) [kg N year-1]

N from compost [kg N year-1]

1990 61 282 228 362 60 236

1991 83 090 309 630 98 742

1992 92 013 342 881 172 251

1993 122 501 456 489 386 072

1994 346 952 1 292 892 558 816

1995 398 929 1 486 580 694 352

1996 437 278 1 629 485 778 047

1997 556 561 2 073 984 732 696

1998 654 736 2 439 826 761 553

1999 895 379 3 336 562 785 463

2000 1 055 616 3 933 677 875 945

2001 1 204 893 4 489 945 966 428

2002 1 339 552 4 991 742 1 050 323

2003 1 444 299 5 382 074 1 097 984

2004 1 546 122 5 761 510 1 133 292

2005 1 627 933 6 066 373 1 137 307

2006 1 702 052 6 342 572 1 100 971

2007 1 875 428 6 988 645 1 114 044

2008 1 932 893 8 227 318 1 158 411

2009 1 980 591 9 745 371 1 231 597

2010 2 028 231 9 163 634 1 303 964

2011 2 092 422 8 718 846 1 408 564

2012 2 194 747 9 145 218 1 560 827

2013 2 288 840 9 537 291 1 471 292

2014 2 331 640 9 715 635 1 530 673

2015 2 406 550 10 190 403 1 504 839

2016 2 492 978 8 559 247 1 637 533

2017 2 060 878 9 326 988 1 641 556

2018 2 068 188 9 360 074 1 631 028



Compost

Activity data for agricultural compost application was derived by expert judgement by Umwelt-bundesamt (2015) on the basis of treated amounts and application pathways (BUCHGRABER et al. 2003) and (EGLE et al. 2014). Based on (LANDWEHR 2000; KRANERT & LANDWEHR 2010; RÖMPP 1996–1999) and (BRUNSTERMANN 2007) an organic mass loss of 50% during the com-posting process has been applied. For compost a dry matter content of 40% (RÖMPP 1996–1999) was used. The N-content of dry matter of 1.4% was derived from (AMLINGER et al. 2005).

Total amounts of compost (composting plants and home composting) were taken from Table 294 (chapter waste). Based on (BUCHGRABER et al. 2003 and EGLE et al. 2014) a share of 45% of the compost from composting plants is applied in sector agriculture. The dry matter content of 40% for compost is derived from (RÖMPP 1996–1999).

Table 288: Amount of compost (dry matter) produced in Austria, 1990–2018.

Year Total amount of compost

[t dm]

agriculturally applied [t dm]

agriculturally applied [%]

Applied compost N [t N]

1990 83 561 4 303 5.1 60

1991 90 673 7 053 7.8 99

1992 119 341 12 304 10.3 172

1993 163 281 27 577 16.9 386

1994 205 698 39 915 19.4 559

1995 230 215 49 597 21.5 694

1996 246 700 55 575 22.5 778

1997 248 815 52 335 21.0 733

1998 260 179 54 397 20.9 762

1999 271 131 56 104 20.7 785

2000 293 394 62 568 21.3 876

2001 342 284 69 031 20.2 966

2002 390 128 75 023 19.2 1 050

2003 432 221 78 427 18.1 1 098

2004 472 354 80 949 17.1 1 133

2005 474 990 81 236 17.1 1 137

2006 470 750 78 641 16.7 1 101

2007 473 800 79 575 16.8 1 114

2008 483 450 82 744 17.1 1 158

2009 496 492 87 971 17.7 1 232

2010 504 530 93 140 18.5 1 304

2011 521 839 100 612 19.3 1 409

2012 546 948 111 488 20.4 1 561

2013 533 965 105 092 19.7 1 471

2014 545 256 109 334 20.1 1 531

2015 543 623 107 489 19.8 1 505

2016 568 005 116 967 20.6 1 638

2017 570 122 117 254 20.6 1 642

2018 569 757 116 502 20.4 1 631



5.5.4 Urine and dung deposited by grazing animals (NFR 3.D.a.3)

Key Category: No

Emissions of ammonia (NH3)

Cattle and Swine

The emission factor of 0.05 kg NH3-N/kg N excreted has been taken from (Eidgenössische For-schungsanstalt 1997).

The share of N excreted on pastures is presented in Table 246 to Table 248. Free range sys-tems for pigs are uncommon in Austria, there are no emissions occurring from that source.

Nitrogen excretion values of cattle and swine are presented in Table 254. Sheep, goats, horses, poultry and other animals

Tier 2 default NH3-N EFs have been taken (EEA 2019, Table 3.9). For other animals (furred game) the EF of sheep has been used. N-excretion values and TAN proportion are described in chapter 5.3.3. Emissions of nitric oxide (NOx)

The Tier 1 methodology does not distinguish between emissions from manure applied to land (3.D.a.2.a) or those from excreta deposited during grazing (3.D.a.3). For each livestock catego-ry, the emissions are reported under 3.D.a.2.a. NOx emissions from grazing are reported as IE (included elsewhere). Emissions of non-methane volatile organic compounds (NMVOC)

In submission 2019 NMVOC emissions from category 3.D.a.3 Urine and dung deposited by grazing animals were reported for the first time. In contrast to the EMEP/EEA Tier 1 methodolo-gy which includes only NMVOC emissions from feeding, the Tier 2 approach comprises EF for buildings (feeding, housing and storage), manure application and grazing. Thus, improved cal-culations resulted in emission estimates for grazing.

For further details on methodologies and parameters used please refer to sub-sector 3.B Ma-nure management, chapter 5.3.7.

5.5.5 Cultivated crops (3.D.e)

Key Category: No

5.5.5.1 NMVOC emissions from vegetation

The Tier 2 methodology according to the EMEP/EEA GB 2019 has been applied. Austria esti-mates emissions for all of the relevant crop types for which EFs are available in the 2019 EMEP/EEA Guidebook (wheat, rye and rape) (see Table 3.3). For the remaining cropland area an average of the highest and lowest EF (wheat and rape) was applied (0.83 kg NMVOC/ha), as recommended in the NEC Review 2017 (EC 2017). Austria has cold climate conditions. The average temperature in Austria varies from 8.4 °C in Klagenfurt to 10.5 °C in Vienna. Grassland is predominately located in mountainous (cold) regions. Therefore, the emission factor for grass (15 °C) of 0.41 kg NMVOC/ha/yr following the EMEP/EEA GB 2019, Table 3.3, has been taken. Emissions are calculated with the following formula.



ENMVOC_cl_gl = ΣAcl,gl * EFcl,gl ENMVOC_cl,gl = annual NMVOC emission flux from cropland and grassland areas (kg NMVOC) Acl,gl =annual cropland area, annual grassland area (ha) EFcl,gl =EF of wheat, rye, rape and average EF (wheat and rape) for cropland and grass (15°C)

for grassland (kg NMVOC/ha)

Activity data

Data of agricultural land use are taken from (STATISTIK AUSTRIA 1990–2019) and (STATISTIK AUSTRIA 2018e). Land use areas (cropland, grassland, alpine grassland) are harmonized with sector Land Use, Land Use Change and Forestry (LULUCF) of Austria’s GHG inventory to be consistent within the Austrian Inventory and across all sectors. Cropland areas are based on data from the national FSS (Farm Structure Survey) and IACS (Integrated Administration and Control System).

In the years when the full FFS was conducted (1990, 1995, 1999 and 2010) these data were taken (ÖSTAT 1991, 1998, STATISTIK AUSTRIA 2001, 2013). In some intermediate years ran-dom sample Farm Structure Surveys were carried out (1993, 1997, 2003, 2005, 2007, 2013 and 2016 – sources: ÖSTAT 1994, 1998, STATISTIK AUSTRIA 2005, 2006, 2008, 2014, 2018f), and these data for cropland area were also taken.

For the years between the full and random sample surveys the data have been interpolated. The data of the random sample farm structure survey 2016 (STATISTIK AUSTRIA 2018e) are con-sidered in this submission. In the 2015 submission an improvement of areas of alpine pastures was carried out, which led to reduced areas of alpine pastures compared to previous surveys. A detailed description of the recalculation of the alpine grassland area is included in 2015 submis-sion (UMWELTBUNDESAMT 2015).

Further details are given in “Austria’s National Inventory Report 2020, chapters 6.3.2 Cropland (Category 4.B) and 6.4.2 Grassland (Category 4.C) (UMWELTBUNDESAMT 2020a).

As recommended under the NEC Review 2018 (EC 2018), the cultivated area of wheat, rye and rape is now included in the following table.

Table 289: Agricultural land use data 1990–2018 for calculating NMVOC emissions (3.D.e).

Year Land Use Areas [ha] Cropland

(total) Wheat Rye Rape Remaining

Cropland Grassland

(total) Grassland (extensive)

1990 1 405 141 278 226 93 041 40 844 993 030 1 714 917 455 692 1991 1 423 377 271 068 85 070 45 552 1 021 687 1 713 391 449 508 1992 1 414 742 245 728 69 114 49 919 1 049 981 1 711 865 443 325 1993 1 398 526 240 971 73 701 59 090 1 024 764 1 710 340 437 141 1994 1 402 750 240 961 77 021 71 402 1 013 366 1 689 668 430 957 1995 1 404 248 255 910 76 826 89 246 982 266 1 668 997 424 773 1996 1 414 005 247 602 51 222 64 904 1 050 277 1 670 182 418 899 1997 1 397 357 259 832 57 807 54 897 1 024 821 1 671 366 413 025 1998 1 395 643 264 405 59 282 52 086 1 019 870 1 661 034 407 151 1999 1 395 274 260 579 55 901 65 768 1 013 026 1 650 702 401 277 2000 1 377 934 293 806 52 473 51 762 979 893 1 652 301 398 499 2001 1 375 899 287 777 51 219 56 098 980 805 1 653 900 395 720 2002 1 374 930 288 764 47 145 55 383 983 638 1 655 499 392 942



Year Land Use Areas [ha] Cropland

(total) Wheat Rye Rape Remaining

Cropland Grassland

(total) Grassland (extensive)

2003 1 375 823 272 001 40 003 44 035 1 019 785 1 657 097 390 163 2004 1 403 797 290 174 45 664 35 284 1 032 675 1 632 873 387 385 2005 1 405 234 288 960 42 847 35 251 1 038 176 1 608 648 384 607 2006 1 389 960 284 577 26 924 42 582 1 035 877 1 581 383 381 828 2007 1 388 741 292 976 46 702 48 509 1 000 554 1 554 118 379 050 2008 1 376 689 296 775 53 171 56 056 970 687 1 539 169 376 271 2009 1 375 326 309 034 48 528 56 933 960 831 1 524 220 373 493 2010 1 372 530 302 852 45 699 53 803 970 176 1 509 271 370 714 2011 1 369 819 304 334 45 943 53 636 965 905 1 493 892 367 997 2012 1 365 214 308 179 48 525 55 821 952 688 1 478 512 365 279 2013 1 364 057 297 286 56 108 58 557 952 106 1 463 133 362 562 2014 1 359 738 304 645 48 241 52 816 954 036 1 434 736 358 957 2015 1 354 301 302 965 39 563 37 529 974 244 1 406 339 355 351 2016 1 344 481 315 088 37 312 39 662 952 418 1 377 942 351 746 2017 1 336 815 295 029 34 476 40 502 966 808 1 377 942 351 746 2018 1 335 080 292 654 40 725 40 504 961 197 1 377 942 351 746

5.5.6 Use of Pesticides (3.D.f)

Until submission 2019 Austria reported NA for source category 3.D.f Use of pesticides. Follow-ing a recommendation of the NEC Review 2019 Austria investigated the list of active substanc-es for which impurity factors are provided in Table 4 of the EMEP/EEA Guidebook 2019, chap-ter 3.D.f., 3.I Agriculture other including use of pesticides.

Activity data

According to Regulation 1185/2009 in Austria the following substances were used in the follow-ing years: Atrazine: 1990–1995 Clopyralid: 1990–2018 Chlorothalonil: 1990–2018 DCPA, Dacthal, Chlorthaldimethyl: 1995 Endosulfan: 1990–2006 Lindane: 1990–1997 Picloram: 1990–2018 Simazine: 1990–2004 For emission calculation activity data on the level of active substances were used. However, in Austria these data are confidential. Thus, Table 42 provides the total amount of active sub-stances.



Table 290: Annual total amounts of active substances containing HCB as impurity in Austria.

Year Active substances [kg]

Year Active substances [kg]

1990 463 422.21 2005 18 272.22 1991 463 422.21 2006 20 818.25 1992 346 793.14 2007 20 167.30 1993 326 005.19 2008 20 593.00 1994 37 396.88 2009 18 515.00 1995 34 867.60 2010 21 309.00 1996 32 188.70 2011 16 881.00 1997 28 727.40 2012 15 395.87 1998 20 357.40 2013 19 376.60 1999 19 586.00 2014 20 053.55 2000 22 767.50 2015 6 673.52 2001 24 055.40 2016 26 415.45 2002 20 584.22 2017 46 821.32 2003 20 099.60 2018 39 569.96 2004 19 850.80

Methodology

Austria applies the EMEP/EEA 2019 Tier 1 default approach and the proposed maximum HCB-concentrations (impurity factors) in active substances according to the EMEP/EEA Guidebook 2019, Table 4.

Depending on the usage of specific substances in the time series the implied impurity factors vary from about 8 mg/kg to 175 mg/kg active substance.



Livestock data (3.B, 3.D) Livestock numbers of poultry and other animals (mainly deer) have been revised as new data has become available based on the final results of the farm structure survey 2016 (STATISTIK AUSTRIA 1990-2019, see Chapter 1.3.8)

Detailed raw material and energy balances (3.D.a.2.c) In 2019 new information on input materials for Austria’s biogas plants became available (E-CONTROL 2019) resulting in slightly revised amounts of digested manure and energy crops.



Methodological changes

NH3

3.D.a.1 Inorganic N fertilisers Revised emissions from inorganic N fertilisers are due to the implementation of new information on agriculture practice. Including the rapid incorporation of urea into the soil in Austria’s calcula-tions resulted in lower NH3 emissions from synthetic fertiliser application for the entire time se-ries (– 0.6 kt NH3 in 2017).

3.D.a.2.a Animal manure applied to soils NH3 emissions of animal manure applied on soils have been revised downwards for the entire time series. The main reasons are updated NH3 emission factors for manure spreading for the livestock categories layers and broilers according to the EMEP/EEA GB 2019, as well as im-provements carried out in the manure management sector due to the new Guidebook (e.g. up-dated NH3 emission factors and an improved calculation of the immobilised fraction of TAN, see Chapter 6.3.2.1). These changes led to a downward revision of the NH3 emissions by – 1.3 kt for the year 2017.


According to the EMEP/EEA GB 2019, the default Tier 2 NH3 EFs for grazing for the livestock categories sheep and other animals have been revised downwards compared to the 2016 GB. This results in lower NH3 emissions for the whole time series (– 0.06 kt NH3 in 2017).

NOx

3.D.a.2.a Animal manure applied to soils The revisions to the ammonia calculations according to the EMEP/EEA GB 2019 in the manure management sector have led to higher N amounts available for application. As a consequence, NOx emissions of manure application have been resived upwards for the entire time series (+ 0.1 kt NOx in 2017).

NMVOC

3.D.a.2.a Animal manure applied to soils NMVOC emissions from manure application have been estimated based on the 2019 EMEP/EEA Tier 2 methodology which is closely linked to the compilation of the ammonia inven-tory. Therefore, the revisions to the ammonia inventory also had an impact on the NMVOC emissions and resulted in lower emissions for the entire time series (– 0.3 kt NMVOC in 2017).

HCB

3.D.f. Use of Pesticides Following a recommendation of the NEC Review 2019 Austria estimated these emissions for the first time.



5.6 NFR 3.D Particle Emissions from Agricultural Soils

Particle emissions reported under source category 3.D result from the following activities: Certain steps of farm work such as soil cultivation and harvesting (field operations). The cal-

culations are based on the EMEP/EEA GB 2019 Tier 1 methodology (EEA 2019). In accord-ance with the EMEP/EEA Guidebook 2019, chapter 3.D, Table 2.1, emissions are allocated to NFR source category 3.D.c Farm-level agricultural operations including storage, handling and transport of agricultural products.

Agricultural bulk material handling. These emissions are estimated under source category 2.A Mineral Products (see Chapter 4.3) based on (WINIWARTER et al. 2001) and reported un-der NFR source category 3.D.d Off-farm storage, handling and transport of bulk agricultural products.


5.6.1.1 Farm-level agricultural operations including storage, handling and transport of agricultural products (3.D.c)

Emissions of particulate matter from field operations are linked with the usage of machines on agricultural soils. They are considered in relationship with the treated areas. In previous sub-missions Austria calculated its emissions based on a country-specific approach. From submis-sion 2018 onwards, as recommended in the NEC Review 2017 (EC 2017), the EMEP/EEA Tier 1 methodology has been applied.

Activity Data

Data of agricultural land use are taken from (STATISTIK AUSTRIA 1990–2019) and (STATISTIK AUSTRIA 2018e). Land use areas (cropland, grassland, alpine grassland) are harmonized with sector Land Use, Land Use Change and Forestry (LULUCF) of Austria’s GHG inventory to be consistent within the Austrian Inventory and across all sectors. Cropland areas are based on data from the national FSS (Farm Structure Survey) and IACS (Integrated Administration and Control System).

In the years when the full FFS was conducted (1990, 1995, 1999 and 2010) these data were taken (ÖSTAT 1991, 1998, STATISTIK AUSTRIA 2001, 2013). In some intermediate years ran-dom sample Farm Structure Surveys were carried out (1993, 1997, 2003, 2005, 2007, 2013 and 2016 – sources: ÖSTAT 1994, 1998, STATISTIK AUSTRIA 2005, 2006, 2008, 2014, 2018f), and these data for cropland area were also taken.

For the years between the full and random sample surveys the data have been interpolated. The data of the random sample farm structure survey 2016 (STATISTIK AUSTRIA 2018e) are con-sidered in this submission. In the 2015 submission an improvement of areas of alpine pastures was carried out, which led to reduced areas of alpine pastures compared to previous surveys. A detailed description of the recalculation of the alpine grassland area is included in 2015 submis-sion (UMWELTBUNDESAMT 2015).


Further details are given in “Austria’s National Inventory Report 2020, chapters 6.3 Cropland (Category 4.B) (UMWELTBUNDESAMT 2020a).



Table 291: Agricultural land use data 1990–2018.

Land Use Area Data Year arable farm land

[1 000 ha] grassland (intensive

used) [1 000 ha] Year arable farm land

[1 000 ha] grassland (intensive

used) [1 000 ha] 1990 1 405 877 2005 1 405 908 1991 1 423 886 2006 1 390 889 1992 1 415 896 2007 1 389 870 1993 1 399 905 2008 1 377 864 1994 1 403 915 2009 1 375 858 1995 1 404 926 2010 1 373 851 1996 1 414 932 2011 1 370 843 1997 1 397 938 2012 1 365 835 1998 1 396 924 2013 1 364 826 1999 1 395 910 2014 1 360 820 2000 1 378 910 2015 1 354 813 2001 1 376 910 2016 1 344 806 2002 1 375 909 2017 1 337 806 2003 1 376 909 2018 1 335 806 2004 1 404 909

Due to the limited number of measurements, a separate parameterization of different field crops as well as a different treatment of cropland and grassland activities is not yet possible. Thus, as activity data the sum of cropland and intensively used grassland area is taken.

Emission factors

The Tier 1 emission factors for TSP, PM10 and PM2.5 are taken from the EMEP/EEA GB 2019, table 3.1 (EEA 2019).

Emission factors do not include a condensable component (see also chapter 12.3).

5.6.1.2 Off-farm storage, handling and transport of agricultural products (3.D.d)

PM emissions from bulk material handling are estimated under source category 2.A Mineral Products (see Chapter 4.3) but reported under sector 3.D.d Off-farm storage, handling and transport of agricultural products.

A simple methodology was applied. Emissions were estimated multiplying the amount of bulk material by an emission factor. Activity data

Activity data was taken from official Statistik Austria production statistics (see Chapter 4.3, Ta-ble 212). Emission factors

The EMEP/EEA GB 2019 does not provide emission factors for this source category. Emission factors are taken from a national study (WINIWARTER et al. 2001) (see Chapter 4.3, Table 211).




No revisions have been carried out.

5.7 NFR 3.F Field Burning of Agricultural Residues

This category comprises burning straw from cereals and residual wood of vinicultures on open fields in Austria.

Burning agricultural residues on open fields in Austria is legally restricted by provincial law and since 1993 additionally by federal law and is only occasionally permitted on a very small scale. Therefore the contribution of emissions from field burning of agricultural waste to the total emis-sions is very low.


Activity Data

According to the Austrian Chamber of Agriculture (AUSTRIAN CHAMBER OF AGRICULTURE 2018), in Austria about 250 ha were burnt in 2018. This value corresponds to about 0.1% of the relevant cereal area in 2018. For 1990 an average value of 2 500 ha was indicated for Austria’s main cultivation regions (PRESIDENTIAL CONFERENCE OF AUSTRIAN AGRICULTURAL CHAMBERS 2004). The extrapolation to Austria’s total cereal production area gave a value of 2 630 ha.

Activity data of agricultural land use (viniculture area) are taken from (STATISTIK AUSTRIA 1990–2019) and (STATISTIK AUSTRIA 2018e). Land use areas are harmonized with sector Land Use, Land Use Change and Forestry (LULUCF) of Austria’s GHG inventory to be consistent within the Austrian Inventory and across all sectors.


According to an expert judgement from the Federal Association of Viniculture (Bundesweinbau-verband Österreich) the amount of residual wood per hectare viniculture is 1.5 to 2.5 t residual wood and the part of it that is burnt is estimated to be 1 to 3%. For the calculations the upper limits (3% of 2.5 t/ha) have been used resulting in a factor of 0.075 t burnt residual wood per hectare viniculture area.

Table 292: Activity data for field burning of agricultural residues 1990–2018.

Year Viniculture Area [ha] Burnt Residual Wood [t]

1990 58 364 4 377

1991 57 981 4 349

1992 57 599 4 320

1993 57 216 4 291

1994 56 422 4 232

1995 55 627 4 172

1996 54 061 4 055



Year Viniculture Area [ha] Burnt Residual Wood [t]

1997 52 494 3 937

1998 51 854 3 889

1999 51 214 3 841

2000 50 304 3 773

2001 49 393 3 704

2002 48 483 3 636

2003 47 572 3 568

2004 48 846 3 663

2005 50 119 3 759

2006 49 981 3 749

2007 49 842 3 738

2008 47 688 3 577

2009 45 533 3 415

2010 45 480 3 411

2011 45 427 3 407

2012 45 373 3 403

2013 45 320 3 399

2014 45 799 3 435

2015 46 277 3 471

2016 46 756 3 507

2017 46 756 3 507

2018 46 756 3 507

The amount of agricultural waste burned is multiplied with a default or a country specific emission factor.

5.7.1.1 Cereals

NH3, NOx, SO2, NMVOC, CO, TSP, PM10, PM2.5, Cd, Hg, Pb, PAHs

The EMEP/EEA Tier 1 default approach (EEA 2019) referring to the IPCC default method was used. For wheat, barley, oats, rye and other cereals the IPCC default combustion factor for wheat residues provided in Table 2.6 of the 2006 IPCC GL (IPCC 2006) has been applied. For dry matter fraction the Austrian specific value of 0.86 was used (LÖHR 1990). Residue/crop product ratios were calculated on the basis of the IPCC 2006 default methodology (see Austria´s National In-ventory Report 2020, chapter on N from crop residues).

For wheat and barley Tier 2 emission factors are available in the guidebook (EEA 2019, Table 3-3 and Table 3-4). For oats, rye and other grains the EMEP/EEA Tier 1 emission factors were applied.



HCB, dioxin/furan

A country specific method was applied (HÜBNER 2001b). National emission factors were taken from HÜBNER (2001b): PCDD/F .. 50 µg/ha HCB ........ 10 000 µg/ha.

5.7.1.2 Viniculture

NOx, SO2, NMVOC, CO, TSP, PM10, PM2.5, Cd, Pb, PAHs

Calculations follow the EMEP/EEA Tier 2 technology-specific approach provided in the EMEP/EEA Guidebook 2019, chapter 5.C.2 Open burning of waste (EEA 2019). The Tier 2 emission factors for orchard crops were used (EEA 2019, Table 3-3).

NH3

The EMEP/EEA 2019 guidebook does not provide a default emission factor for NH3. In con-sistency to previous submissions the EF of 1.9 kg per ton burnt wood was taken (EEA 2007).

Hg

The EMEP/EEA 2019 guidebook does not provide a default emission factor for Hg. For emis-sion calculation a country specific methodology was used. National emission factors were taken from (HÜBNER 2001a), the dry matter content of residual wood was assumed to be 80%,: Hg ............. 0.038 mg/kg dmwood, 0% remaining in ash HCB, dioxin/furan

A country specific method was applied. The national emission factors per ton burnt wood were taken from (HÜBNER 2001b): PCDD/F .... 12 000 µg/Mg Waste HCB .......... 2 400 µg/Mg Waste


The EMEP/EEA Tier 2 emission factors for orchard crops provided in the guidebook chapter 5.C.2 Small-scale waste burning were used for the first time resulting in revised emissions for NOx, SO2, NMVOC, CO, TSP, PM10, PM2.5, Cd, Pb, and PAHs.

Austria’s Informative Inventory Report (IIR) 2020 – Waste (NFR Sector 5)


6 WASTE (NFR SECTOR 5)

6.1 Sector Overview

This chapter includes information on and descriptions of methodologies applied for estimating emissions of NEC gases, CO, heavy metals, persistent organic pollutants (POPs) and particu-late matter (PM), as well as references for activity data and emission factors concerning waste management and treatment activities reported under NFR Category 5 Waste for the period from 1990 to 2018.

Emissions addressed in this chapter include emissions from the sub categories Solid Waste Disposal on Land (NFR Sector 5.A); Composting (NRF Sector 5.B), comprising composting, mechanical-biological treatment of

waste; and anaerobic treatment of agricultural feedstock, Waste Incineration (NFR Sector 5.C), which comprises the incineration of corpses, municipal

waste and waste oil; Wastewater Handling (NFR Sector 5.D). Other Waste (NFR Sector 5.E), comprising emissions from unwanted fires in cars and vari-

ous types of houses. The following Table 283 presents the contribution of sector Waste to national total emissions of the different pollutants.

Table 293: Contribution to National Total Emissions from NFR sector 5 Waste in 2018.

Pollutant Source Category: 5 Waste Pollutant Source Category: 5 Waste

SO2 0.12% PAH < 0.01%

NOx 0.01% Diox 6.90%

NMVOC 0.05% HCB 0.18%

NH3 2.48% TSP 1.81%

CO 0.60% PM10 1.65%

Cd 0.16% PM2.5 1.93%

Hg 4.09%

Pb 0.01%

The overall emission trend reflects changes in waste management policies as well as waste treatment facilities. According to the Landfill Ordinance132 waste has to be treated before being deposited in order to reduce the organic carbon content. Decreasing amounts of deposited waste result in decreasing NH3 emissions. Although an increasing amount of waste is incinerated, NOx, NMVOC and NH3 emissions from 5.C (waste incineration without energy recovery) are de-creasing. This is because – apart from some clinical and hazardous waste – most waste is combusted in district heating or industrial plants, where the energy is used and emissions are thus allocated to 1.A. Emissions arising from incineration of waste with energy recovery are tak-en into account in NFR Sector 1.A. NH3 emissions arising from category 5.B.1 Composting, be-ing the highest NH3 emission source in this category showed an increasing trend until 2005 due to

132 Verordnung über die Ablagerung von Abfällen (Deponieverordnung), BGBl. Nr. 164/1996, BGBl. II Nr. 49/2004; gel-

tende Fassung: Deponieverordnung 2008 (BGBl. II Nr. 39/2008).



increasing amounts of biologically treated waste, a result of the separate collection of organic waste (regulated in an Austrian act on collection of biogenic waste133) and the obligatory pre-treatment of waste134 since 2004 (with some exemptions until 2009) before deposition (regulat-ed in Austrian Landfill Ordinance135).

The following list comprises primary and secondary measures which were implemented over the last years: Primary measures waste avoidance in households: savings in packaging materials; intensive waste separation

(paper, glass, plastics, metal, biogenic waste; reuse; separate collection of hazardous waste like solvents, paints or (car) batteries).

waste avoidance in industry and energy industry: waste separation regarding material, recy-clable waste, hazardous waste; more efficient process lines; use of co- and by-product pro-cess line; (scap) recycling; substitution of raw material/fuel; reduction in use of raw materi-al/fuel and additive raw material; higher product quality.

recycling of old cars (recycling certificate). Secondary measures general strategy: waste avoidance prior to waste recycling/reuse prior to landfilling; recovery of (recyclable) material from waste like steel and aluminium recycling, and recycling

of paper, glass, plastic; recovery of (recyclable) material from electronic waste; composting of biogenic material; mechanical-biological treatment of waste; fermentation of biogenic material; energetic use in waste incineration.

The following figure shows the main streams of treatment and disposal of waste from households and similar sources. It also aims to transparently show the distinction between residual and non-residual waste (with regard to municipal solid waste136) and to demonstrate that all relevant ac-tivity data are taken into account in the inventory.

133 Verordnung über die getrennte Sammlung biogener Abfälle (BGBl. Nr. 68/1992) 134 Since 2004 respectively – without exemption – 2009 no waste is allowed to be deposited any more without being

pre-treated (in thermal or bio-technical treatment plants) 135 Ordinance on Landfills (Landfill Ordinance 2004), Federal Law Gazette No 164/1996 as amended by Federal Law

Gazette No 49/2004; Ordinance on Landfills (Landfill Ordinance 2008), Federal Law Gazette II No 39/2008 as amended by Federal Law Gazette II No 185/2009

136 In fact non-residual waste also comprises waste from other (industrial) sources.



Figure 46: Main streams of treatment and disposal of waste from households and similar sources.

Almost 100% of waste from households and similar sources is incinerated, recycled or treated mechanical-biologically. Since 2009 only minor amounts of stabilized residues have been still de-posited.


6.2.1 Completeness

Table 284 gives an overview of the NFR categories included in this chapter and also provides information on the status of emission estimates of all sub categories. A “” indicates that emis-sions from this sub category have been estimated.

Treatment and disposal routes 2017

Data sources: BMNT, Graphic: Umweltbundesamt



Table 294: Overview of sub categories of Category 5 Waste and status of estimation.

NFR Category Status NEC gases CO PM Heavy metals POPs

NO

x

SO2

NH

3

NM

VOC

CO

TSP

PM10

PM2.

5

Cd

Hg

Pb

Dio

xin

PAH

HC

B

PCB

5.A Solid Waste Disposal on Land IE* IE* NA NA NA NA

5.B Biological Treatment of Waste (Composting, anaerobic digestion)

NA NA NA NA NA NA NA NA NA NA NA NA NA NA

5.C Waste Incineration

5.D Wastewater Handling NA NA NA NA NA NA NA NA NA NA NA NA NA NA

5.E Other Waste NE NE NA NE NE NE NE NE * related emissions are covered under sector Energy

NOx and SO2 emissions are covered in the energy sector, as most of the collected landfill gas is used for energy recovery.


In the following table the key categories of sector waste are presented.

NFR Category Source Category Key Category Pollutant KS-Assessment

5.E Other waste DIOX LA, TA

6.2.3 Methodology

In general the CORINAIR simple methodology, multiplying activity data for each sub category with an emission factor, is applied. For waste disposal the IPCC methodology (FOD method) was used to calculate the amount of landfill gas, the methodology is described in detail below.


The uncertainties determined for air pollutants largely correspond to those of greenhouse gases as underlying data is the same in most cases. The assessment for 5.A Solid Waste Disposal is based on a national study (WINIWARTER 2007). The uncertainties have been determined based on the following considerations IPCC Tier 2 method applied; Country-specific activity data taken from Austrian databases; Availability of data on landfill recovered on a regular basis.



Table 295: Uncertainty assessment for waste subcategories.

Activity data Emission factor

5.A Solid Waste Disposal on Land – NH3, NMVOC

12% 25%

5.A Solid Waste Disposal on Land – PM2.5 12% 200%

5.B Biological Treatment of Waste – NH3 20% 125%

5.C Waste Incineration – NH3, NMVOC 7% 125%

5.C Waste Incineration – PM2.5, NOx, SO2 7% 200%

5.D Waste water treatment and discharge 20% 50%

5.E Other Waste 50% 200%


To ensure, that most up-to-date data and parameters (e.g. landfill gas recovery, connection rate etc.) are considered, national waste experts, mostly within Umweltbundesamt are contacted. Af-ter finalisation of the calculation but prior to submission, the respective section of the IIR is sent to relevant experts for a final check of descriptions and trend analysis. Moreover, activity data is checked for plausibility and time series consistency. If dips and jumps exceeding 20 % com-pared to the year before are observed, other experts or data providers are consulted to either provide the explanation or to identify a possible inconsistency or an error. Recalculations are validated in detail by comparing several parameters and partial results over the whole time series. Explanations for recalculations are documented.

Input Data Audit 2014/2015

End of 2014/beginning 2015 a multi-step audit was conducted at the BMLFUW (Department re-sponsible for analysis and quality check of EDM data on landfilled waste) and Umweltbun-desamt (Department responsible for data query on behalf of the BMLFUW). The aim was to get insight into collection, processing and quality control of data, i.e. waste amounts deposited, and to clarify issues on transparency, accuracy, completeness, consistency, comparability and time-ly availability of data. The audit focused on waste amounts deposited, but partly also covered the data basis and procedures for the compilation of data on waste amounts composted. The audit showed a very strong commitment on quality. There is close cooperation with relevant da-ta providers, in particular related to waste treating facilities. QA/QC takes place at different stages, and an improvement program ensures adaption of the system to changing require-ments. Some recommendations on improvements have been given by the IBE, but mainly with regard to documentation and archiving.




6.3 NFR 5.A Waste Disposal on Land

6.3.1 NMVOC, NH3, CO and heavy metals emissions


NFR 5.A.1 Managed waste disposal on land accounts for the main source of NMVOC emissions of NFR Category 5 Waste. In Austria all waste disposal sites are managed landfills.

In the Austrian inventory two main categories of waste are distinguished: residual waste and non-residual waste. Residual waste refers only to the part of municipal solid waste137 collected by the municipal system (mixed composition) that is directly deposited without any pre-treatment. Non-residual waste comprises among others municipal solid waste having been pre-treated, sludges from wastewater treatment and waste from industrial sources.

‘Residual waste’ corresponds to waste: originating from households and similar sources (private households, administrative facilities

of commerce, industry and public administration, kindergartens, schools, hospitals, small en-terprises, agriculture, market places and other generation points)

remaining after separation of paper, glass, plastic etc. at the source covered by the municipal waste collecting system directly landfilled without having passed any pre-treatment

It has to be noted that from 2009 it is not allowed to deposit waste without prior pre-treatment (due to the Landfill Ordinance138), so since 2009 no disposal of ‘residual waste’ is reported by landfill operators and therefore no new depositions of residual waste is taken into account in the inventory. Emissions from this subcategory are therefore only affected by historical depositions.

Waste from households and similar sources covered by the municipal waste collection system but undergoing a pre-treatment before deposition is not included in this category, but in category “non-residual waste” (sub-category “sorting residues”, among others from mechanical-biological treatment) and in sector “energy” respectively, as also waste incineration is a pre-treatment option.

‘Non-residual waste’: comprises pre-treated waste from households (e.g. residues from mechanical-biological

treatment) and waste with biodegradable lots from other (industrial) sources is divided into the categories wood, construction waste, paper, green waste, sludge, sorting

residues/stabilized material (incl. bulky waste), textiles and fats

Stabilized material and sorting residues remaining after mechanical, biological and mechanical-biological treatment and bulky waste are the main fraction deposited (98%). Some minor amounts of sludge, construction waste and paper with little TOC content (below the threshold for TOC disposal) are landfilled as well. Green waste, paper and wood are mainly composted, recycled or reused due to the implementation of the Waste Management Law, fats and textiles are not deposited any more.

137 i.e. waste from households as well as other waste which, because of its nature or composition, is similar to waste

from household (Article 2 (b): Council Directive 1999/31/EC of 26.April 1999 on the landfill of waste). 138 Ordinance on Landfills (Landfill Ordinance 2004), Federal Law Gazette No 164/1996 as amended by Federal Law

Gazette No 49/2004; Ordinance on Landfills (Landfill Ordinance 2008), Federal Law Gazette II No 39/2008 as amended by Federal Law Gazette II No 185/2009




The anaerobic degradation of land filled organic substances results in the formation of landfill gas.

NMVOC and NH3 emissions are calculated based on their respective content in the emitted landfill gas (after consideration of gas recovery). In a first step the amount of methane production is cal-culated applying the first order decay model for nine different waste fractions (residual waste, green waste, paper, etc.). In a second step the amount of landfill gas collected is deducted. In a third step the remaining amount of methane in landfill gas is converted to the amount of landfill gas using the density of methane and the concentration of methane in the landfill gas. Finally this amount of landfill gas is multiplied with the respective emission factors (see Table 291).

For NMVOC a concentration of 300 mg per m³ landfill gas, for NH3 a concentration of 10 mg per m³ landfill gas is assumed.

The amount of generated landfill gas from disposed solid waste is calculated by taking into ac-count: the amounts of deposited waste, reported by landfill operators for different waste categories, the carbon contents of each waste fraction and several other parameters, among others on landfill gas recovery139.

For the calculation of emissions the IPCC Tier 2 method (First Order Decay) is applied, consist-ing of two equations: first, calculating the amount of methane accumulated up to the year of the inventory; second, calculating the emitted methane after subtracting the recovered and oxidised methane amounts. As far as available country-specific parameters are taken (e.g. the recovered landfill gas).

Activity data For emissions calculation waste deposited from 1950 onwards has been taken into account. Table 286 presents the waste amounts considered 1990–2018.

Table 296: Activity data for “Residual waste” and “Non-Residual Waste” 1990–2018.

Year Non-Residual waste [t] Residual waste [t] Total waste [t]

1990 648 702 1 995 747 2 644 448 1991 661 676 1 799 718 2 461 394 1992 674 909 1 614 157 2 289 067 1993 688 407 1 644 718 2 333 126 1994 702 175 1 142 067 1 844 242 1995 716 219 1 049 709 1 765 928 1996 730 543 1 124 169 1 854 713 1997 745 154 1 082 634 1 827 788 1998 760 057 1 081 114 1 841 171 1999 822 179 1 084 625 1 906 804 2000 826 874 1 052 061 1 878 935 2001 772 786 1 065 592 1 838 378 2002 792 753 1 174 543 1 967 296 2003 890 640 1 385 944 2 276 584 2004 344 747 282 656 627 403

139 Most active landfills in Austria have gas collection systems – regulated in §31 Landfill Ordinance (Federal Law Ga-

zette BGBl. Nr 39/2008.



Year Non-Residual waste [t] Residual waste [t] Total waste [t]

2005 389 660 241 733 631 393 2006 425 091 260 068 685 159 2007 464 109 154 517 618 626 2008 319 927 129 324 449 251 2009 256 340 0 256 340 2010 244 969 0 244 969 2011 273 313 0 273 313 2012 166 263 0 166 263 2013 185 156 0 185 156 2014 174 500 0 174 500 2015 131 959 0 131 959 2016 132 182 0 132 182 2017 151 866 0 151 866 2018 163 663 0 163 663

1990–2018 -75% -100% -94%

In 1990, the Austrian Waste Management Law140 entered into force. As a consequence, from 1990 to 1995, the deposited amount of waste decreased due to recycling activities, reuse and increased capacities for waste combustion, despite a rise in total waste generation. After 1994/1995 waste recycling still increased but was compensated by growing amounts of total waste generated so the amounts of deposited waste did not decrease any further. The amount of deposited waste peaked in 2003 due to the remediation of some contaminated sites and then dropped as from the beginning of 2004 only pre-treated waste was allowed to be deposited. This is due to the implementation of the Landfill Ordinance, which prohibits the disposal of un-treated waste and therefore leads to reduced waste volumes as well as decreased carbon con-tent in deposited waste.

However, under certain circumstances there were some exceptions to this pre-treatment-obligation granted to some Austrian provinces.141 In four of the nine Austrian provinces it was still allowed to deposit waste directly without any pre-treatment until the end of 2008. From 2009 on, no residual waste142 is allowed to be deposited any more.

140 Waste Management Act of 2002 , Federal Law Gazette I No 102/2002 as amended by Federal Law Gazette I

No 9/2011 141 Regulated in § 76.Abs. 7 AWG 2002 142 as defined at the beginning of this sub-chapter



Figure 47: Deposited waste (residual and non-residual waste) 1990–2018.

The quantities of “residual waste” have been taken from the following sources: Data for 2008–2018 have been taken from the EDM143, an electronic database administered

by the BMNT. Since the beginning of 2009 landfill operators are obliged to register their data directly and electronically (per upload) at the portal of http://edm.gv.at145.

Data for 1998–2007 were taken from a database for solid waste disposals called “Deponie-datenbank” (‘Austrian landfill database’), a database administered and maintained by Um-weltbundesamt until the end of 2008.

Data for 1950–1997 on the amounts of deposited residual waste were taken from national studies (HACKL & MAUSCHITZ 1999, UMWELTBUNDESAMT 2001b) and the respective Federal Waste Management Plans (BMFLUW 1995, BMLFUW 2001).

In the national study (HACKL & MAUSCHITZ 1999) as well as in the Federal Waste Management Plans the amounts of residual waste from administrative facilities of businesses and industries were not considered and therefore originally not included in the data of the years 1950 to 1999. Waste from these sources is however deposited and hence reported by the operators of landfill sites (therefore included in the Austrian landfill database) and thus considered in the time series from 1998 onwards. To achieve a consistent time series, data of the two overlapping years146 (1998 and 1999) were examined and the difference – which represents the residual waste from administrative facilities of industries and businesses – was calculated. This difference, relative to the change of residual waste from households, was then applied to the years 1950 to 1997 accordingly.

143 Electronic Data Management 144 According to § 41 (1) Landfill Ordinance, Federal Law Gazette BGBl. Nr 39/2008 145 According to §41 (1) Landfill Ordinance, Federal Law Gazette BGBl. Nr 39/2008 146 Data available from the Federal Waste Management Plan (Bundesabfallwirtschaftsplan - BAWP) as well as from the

Austrian landfill database.

0

500.000

1.000.000

1.500.000

2.000.000

2.500.000

3.000.000

3.500.000

1950

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

2009

2011

2013

2015

2017

tota

l was

te d

epos

ited

[t]

Waste deposited


http://edm.gv.at/



The quantities of “non-residual waste” from 1998 to 2007 were taken from the database for solid waste disposal “Deponiedatenbank” (“Austrian landfill database”), the values for 2008 onwards were taken from the EDM147 (Electronic Data Management). Only the amounts of waste with bi-odegradable lots were considered. Table 287 presents a summary of all considered waste types and the corresponding numbers (list of waste). For calculating the emissions of residual waste the waste types were aggregated to the categories wood, paper, sludge, other waste, bio waste, textiles, construction waste and fats. There are not any data available for the years before 1998. Thus an extrapolation was carried out using the Austrian GDP (gross domestic product) per in-habitant (KAUSEL 1998) as indicator. In order to get a more robust estimate a 20 year average value was applied.

Table 297: Considered types of waste (list of waste148).

Waste Identi-fication No

Type of Waste Waste Identi-fication No

Type of Waste

0303 wastes from pulp, paper and card-board production and processing

170204 Glass, plastic and wood containing or contam-inated with dangerous substances

1905 wastes from aerobic treatment of solid waste

170903 other construction and demolition wastes (in-cluding mixed wastes) containing dangerous substances

1908 wastes from wastewater treatment plants not otherwise specified

170904 mixed construction and demolition waste

1909 wastes from the preparation of wa-ter intended for human con-sumption or water for industrial use

190805 sludge from treatment of urban wastewater

1912 wastes from the mechanical treat-ment of waste (for example sorting. crushing. compacting. pelletising) not otherwise specified

190809 grease and oil mixture from oil/water separa-tion containing only edible oil and fats

20303 waste from solvent extraction 200101/ 200102

paper and cardboard

30105 Sawdust, shavings, cuttings, wood, particle board and veneer

200108 biodegradable kitchen and canteen waste

30304 de-inking sludge from paper recy-cling

200111 textiles

30307 mechanically separated rejects from pulping of waste paper and cardboard

200201 Bio-degradable wastes

30310 fibre rejects, fibre-, filler-. and coat-ing sludge from mechanical sepa-ration

200302 waste from markets

40106 Sludge, in particular from on-site effluent treatment containing chromium

200307 bulky waste

40109 waste from dressing and finishing 190811–14 sludge from treatment of industrial wastewater 40221 wastes from unprocessed textile fi-

bres 200125 edible oil and fat

150103 wooden packaging 170201 wood

147 Electronic Data Management (EDM): part of the eGovernment-strategy of the Austrian Government, registration re-

quirements and reports in the field of environ-ment.https://secure.umweltbundesamt.at/edm_portal/home.do?wfjs_enabled=true&wfjs_orig_req=/home.do

148 Commission Decision of 3 May 2000 replacing Decision 94/3/EC establishing a list of wastes pursuant to Article 1(a) of Council Directive 75/442/EEC on waste and Council Decision 94/904/EC establishing a list of hazardous waste pursuant to Article 1(4) of Council Directive 91/689/EEC on hazardous waste.

https://secure.umweltbundesamt.at/edm_portal/home.do?wfjs_enabled=true&wfjs_orig_req=/home.do



Methodology

Where available, country specific factors are used. If these were not available IPCC default val-ues are taken. Table 288 summarises the parameters used and the corresponding references.

Table 298: Parameters for calculating landfill gas from SWDS.

Waste category/ Parameters re

sidu

al w

aste

woo

d

pape

r

slud

ges

Sort

ing

resi

dues

/ ou

tput

MB

T149 /

bulk

y w

aste

Bio

-was

te

text

iles

Con

stru

ctio

n w

aste

fats

Methane correction factor (MCF)

1 IPCC default for managed SWDS

Fraction of degradable organic carbon dissimilated (DOCF)

0.6 0.5 0.55 0.55 0.55 0.55 0.55 0.55 0.77

national waste expertise (UMWELTBUNDESAMT 2005b)150

DOC (kt C/kt waste)

see Table 290

0.45 0.3 0.11 0.16 0.16 0.5 0.09 0.2

(BAUMELER et al. 1998) (UMWELTBUNDESAMT 2005b)

Half life period (t1/2)

7 25 15 7 20 10 15 20 4

Nat

iona

l was

te

expe

rts

(GIL

BE

RG

et a

l. 20

05)

(GIL

BE

RG

et a

l. 20

05)

Ass

umpt

ion:

sam

e as

resi

dual

was

te

IPC

C d

efau

lt sl

ow

deca

y

Ass

umpt

ion:

sim

ilar

to p

aper

Ass

umpt

ion:

sam

e as

pap

er

IPC

C d

efau

lt sl

ow

deca

y

(GIL

BE

RG

et a

l. 20

05)

Fraction of CH4 in Landfill Gas (F)

0.55 as cited in various Austrian and German literature (FLÖGL, W. 2002, ÖWAV 2003,

LFU 1992, UMWELTBUNDESAMT (2008a) UMWELTBUNDESAMT (2014b) Methane Oxidation in the upper layer (OX)

10% IPCC default

Landfill gas recovery (R)

see Figure 50 (UMWELTBUNDESAMT 2004b, 2008, 2014b, 2019b)

Process start (M) 13 Delay time of 6 months, with an average residence time of 6 months (IPCC default)

149 MBT: Mechanical-biological treatment 150 Higher DOCf values than 0.5 (the IPCC 2006 default) are applied for most of the waste types (except wood) as the

composition data shows a low share of lignin in the waste deposited. The DOCf for fats is set to 0.77 as lignin C is excluded here. The lower share of lignin C deposited can be justified by the fact that in Austria a high share of e.g. garden or park waste is treated biologically (considered under 5.B.1 composting).



Biodegradable organic carbon (DOC)

The DOCs of the different waste categories under ‘non-residual waste’ are constant for the en-tire time series and are shown in Table 288. As these categories are clearly defined (wood, pa-per, sludge etc.) and can therefore be considered as quite ‘homogenous’, there was no need to change the DOC over the years.

Figure 48: DOC of non-residual waste fractions.

The DOC of ‘residual waste’ however has changed over the years in accordance with its chang-ing composition. The separate collection of biogenic waste, paper and cardboard, and glass, and the increase of food waste in recent years etc. has clearly influenced the trend of the DOC.

For the year 1990, a DOC content of 200 g/kg residual waste was taken (UMWELTBUNDESAMT 2003c). For 2008, the last year in which this waste category has been deposited, the DOC was 169 g/kg waste. It was calculated on basis of updated information on the composition of residual waste published in the Annual update (2009) of the Federal Waste Management Plan 2006 (BMLFUW 2006a), taking into account the different carbon content of the fractions as published in (UMWELTBUNDESAMT 2003c). From 2009 on, only pre-treated waste, referred to as non-residual waste, is allowed to be deposited in Austria. Hence, only historical amounts are relevant and the DOC does not need to be updated any more.

0.45

0.30

0.11

0.16

0.16

0.50

0.09

0.20

wood

paper

sludges

residues

biowaste

textiles

construction waste

fats

DOC (kt C/kt waste)




Figure 49: Development of DOC in residual waste.

The decrease during the 1990ies in DOC-content was due to the introduction of separate collec-tion of bio-organic waste and paper waste. The amount of bio-waste that is collected separately increased over the time, while the organic share in residual waste decreased. This resulted in a change of waste composition with the effect of a decreasing DOC content. Since 2000 biogenic components in residual waste are increasing; this is due to the increasing share of biogenic components, especially of food waste, in residual waste.

Table 289 presents the composition of residual waste for several years between 1990 and 2008. On the basis of this information a time series for DOC was estimated (see Table 290). For the years before 1990, the same DOC as in 1990 was used.

Table 299: Composition of residual waste.

Residual waste 19901) 19961) 19991) 20042) 20083) [% of moist

mass] [% of moist

mass] [% of moist

mass] [% of moist

mass] [% of moist

mass] Paper, cardboard 21.9 13.5 14 11 12 Glass 7.8 4.4 3 5 4 Metal 5.2 4.5 4.6 3 3 Plastic 9.8 10.6 15 10 10 Composite materials 11.3 13.8 – 8 10 Textiles 3.3 4.1 4.2 6 6 Hygiene materials – – 12 11 8 Biogenic components 29.8 29.7 17.8 37 40 Hazardous household waste

1.4 0.9 0.3 2 1

Mineral components 7.2 3.8 – 4 3 Wood, leather, rubber, other components

2.3 1.1 2.6 1 –

Residual fraction – 13.6 26.5 2 2 1) (UMWELTBUNDESAMT 2003c) 2) (BMLFUW 2006a) 3) Annual update (2009) of the Federal Waste Management Plan (BMLFUW 2006a)

-

50

100

150

200

250

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

orga

nic

carb

on

in re

sidu

al w

aste

[g/k

g]

DOC in Residual Waste




Table 300: Time series of bio-degradable organic carbon content (DOC) of residual waste (mixed MSW, directly deposited)

Year kt C/kt Residual Waste Year kt C/kt Residual Waste

1950–1959 0.20 1) 1998 0.13 2)

1960–1969 0.20 1) 1999 0.12 2)

1970–1979 0.22 1) 2000 0.13 *)

1980–1989 0.21 1) 2001 0.14 *)

1990 0.20 2) 2002 0.15 *)

1991 0.19 2) 2003 0.16 *)

1992 0.18 2) 2004 0.17 3)

1993 0.17 2) 2005 0.17 *)

1994 0.16 2) 2006 0.17 *)

1995 0.15 2) 2007 0.17 *)

1996 0.14 2) 2008 0.17 4)

1997 0.13 2) 2009–2018 n.r.**) 1) assumed to be equal to the DOC of 1990 2) (UMWELTBUNDESAMT 2003c) 3) calculated according to waste composition 2001 (BMLFUW 2006a) 4) calculated according to waste composition 2009 (Status Report to BMLFUW 2006a) *) interpolated values (2000–2003) and (2005–2007) **) no deposition of residual waste any more

Decomposable DOC fraction (DOCf)

The DOCf values used for calculation are shown in Table 288.

Austria does not apply the bulk DOCf option of the IPCC 2006 GL as detailed information is available on the waste deposited. The composition of the different landfilled waste fractions (waste types) is well known, allowing for adapting the default DOCf (0.5) as provided by the IPCC 2006 GL accordingly (see UMWELTBUNDESAMT 2005b). Higher DOCf values than the IPCC 2006 default (0.5) are applied for most of the waste types (except wood) as the composition da-ta shows a low share of lignin in the waste deposited. The DOCf for fats is set to 0.77 as lignin C is excluded here.

The higher DOCf values used compared to the bulk DOCf can be justified by the fact that in Austria a high share of e.g. garden or park waste (i.a branches from trees and bushes) is treat-ed biologically in composting plants (considered under 5.B.1 composting).

Landfill gas recovery

In 2004, the Umweltbundesamt investigated the amount of annually collected landfill gas by questionnaires sent to landfill operators (UMWELTBUNDESAMT 2004b), showing that in 2001, the amount of collected landfill gas was more than 5 times higher than in 1990. In 1990 only 9 land-fills were equipped with landfill gas wells. In 2001, at all operating mass landfills landfill gas was collected.



In 2008, 2013 and 2018 further surveys were conducted (UMWELTBUNDESAMT 2008, UMWELT-BUNDESAMT 2014b, UMWELTBUNDESAMT 2019b) to get new data on collected landfill gas as well as information on its use from landfill operators. Results show that from 2002 onwards, the amount of landfill gas recovered decreased (despite a consistent recovery practice) as a conse-quence of the reduced carbon content of deposited waste and consequently reduced landfill gas pro-

duction the slightly decreasing methane concentration in recovered landfill gas151 – an effect that is

due to the extensive capturing of landfill gas which can lead to the dilution of the landfill gas captured.

Compared to 2002 (maximum amount of landfill gas captured), landfill gas recovered decreased by 70% by 2018.

Figure 50: Amount of collected landfill gas 1990 to 2018.

Emission Factors

NMVOC, CO, NH3 and heavy metal emissions are calculated according to their content in the emitted landfill gas (after consideration of gas recovery). 152

Table 301: Emission factors for CO, NMVOC, NH3 and heavy metals.

CO NMVOC NH3 Cd Hg Pb Vol.% mg/Nm3 mg/Nm3 mg/Nm3 mg/Nm3 mg/Nm3

concentration in landfill gas 2 300 10 0.003 0.00002 0.003


No recalculations have been made in this years’ submission. 151 a methane concentration of 55% (default) is used for the estimation of the landfill gas produced (‘F’) over the whole

time-series. 152 according to UMWELTBUNDESAMT (2001b)

-

10

20

30

40

50

60

70

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

2014

2016

2018

land

fill g

as [M

io m

³]

Amount of collected landfill gas

Source: Umweltbundesamt (2004c, 2008a, 2014b, 2019b)



6.3.2 PM emissions


PM emissions reported here are from waste handling at landfill sites. Only specific waste types are considered such as residues from iron and steel production (slags, dusts), clinker, dust and ashes from thermal waste treatment and combustion plants, as well as some mineral and con-struction waste. 6.3.2.2 Methodological Issues

PM emissions are calculated by multiplying the waste amounts with the respective emission fac-tors for TSP, PM10 and PM2.5. Activity Data and Emission Factors

Activity data has been taken from a database for landfill disposal and – since 2008 – the EDM153. For the calculation only specific waste types are considered such as residues from iron and steel production (slags, dust), from thermal waste treatment and combustion plants (clinker, dust and ashes), as well as some mineral and construction waste.

Activities and emissions for the years 1990 and 1995 originate from the national study on par-ticulate matter (WINIWARTER et al. 2007).

Table 302: Activity data (waste amounts deposited) considered for the calculation of particulate matter.

Year residues from iron and steel production (slags,

dusts)

clinker, dust and ashes

mineral waste

construction waste

[t] [t] [t] [t]

1990 7 970 000 1995 8 850 000 1998 65 927 303 384 3 974 912 36 338 1999 29 402 274 628 3 002 883 46 008 2000 37 998 300 914 4 632 071 56 725 2001 43 911 352 403 4 380 050 54 386 2002 147 484 407 571 5 505 821 32 987 2003 172 444 480 221 6 515 947 24 665 2004 96 182 585 360 8 690 991 14 475 2005 156 764 685 349 9 643 097 16 555 2006 159 642 914 500 9 234 534 21 805 2007 150 822 860 544 10 957 137 14 465 2008 163 684 716 616 9 049 317 3 486 2009 85 798 668 522 8 663 035 350 2010 61 929 562 328 10 156 901 471 2011 69 075 596 097 11 805 373 628 2012 71 987 558 869 14 728 289 229 2013 167 368 765 275 14 775 275 619 2014 213 661 962 200 19 011 447 486

153 Electronic Data Management



Year residues from iron and steel production (slags,

dusts)

clinker, dust and ashes

mineral waste

construction waste

[t] [t] [t] [t]

2015 191 802 974 180 23 983 199 27 2016 166 483 703 995 26 051 849 74 2017 161 709 697 007 26 217 884 48 2018 88 882 986 935 26 987 701 31

1998–2018 35% 225% 579% -100%

Amounts of all relevant waste types have increased over the time series, especially mineral waste due to enhanced soil excavation activities. Remarkable increases can also be observed in the iron and steel production as well as the thermal waste treatment and consequently in their residues landfilled.

The following emission factors are used (WINIWARTER et al 2007). Information on the condensa-ble component to be included or excluded in the applied PM emission factors can be found in chapter 12.3.

Table 303: Emission factors for PM.

TSP PM10 PM2.5 g/t WASTE g/t WASTE g/t WASTE

18.00 8.52 2.68


Minor recalculations are reported for particulate matter emissions from waste disposal (-2.5 t TSP, -1.2 t PM10, -0.4 t PM2.5 in 2017) caused by the correction of a transcription error.

6.4 NFR 5.B Composting


In category 5.B, NH3 emissions from mechanical-biological treatment, composting of waste and anaerobic treatment of agricultural feedstock is addressed. NH3 emissions arising from this sub-category increased over the time period as a result of the increasing amount of biologically treated waste.

The amounts of waste treated in composting plants or in home composting plants have in-creased strongly between 1990 and 2005 (+273%), and stabilised since then. For mechanical treatment plants the amounts of waste treated almost doubled between 1990 and 2007, since then a decrease can be observed.

NH3 emissions from composting and from mechanical biological treatment only amount to 1 244 t in 2018.

NH3 emissions from the anaerobic digestion (manure and energy crops) have been considered, and reported under category 5.B.2. For further information on the methodology used please re-fer to sector 3 Agriculture, chapter 5.3.4.



For NH3 emissions resulting from the anaerobic treatment of biowaste and green waste a rough estimate according to the method of the EMEP/EEA Guidebook has been carried out. As a worst case it was assumed that the total amount of waste input into biogas plants consist of biowaste (N content: 0.0068 kgN/kg fresh weight). Using the tier 1 method of the EMEP/EEA guidebook (as no detailed data is available) and the default emission factor (0.0286 kg NH3-N/kg N in the feedstock), the estimate resulted in 105 t NH3 in 2017 (corresponding to a share of 0.15% of the Austrian total NH3-emissions, which is below the threshold of significance). It can be assumed that this is an overestimation as in reality the waste input into biogas facilities does not consist only of biowaste but also to considerable parts of green waste showing a lower N-content. Furthermore, a part of the digestate is separated into a liquid and a solid phase (no de-tailed information available on the amounts). The solid phase is partly composted (included in the emission from composting (5.B.1) and partly combusted (included in 1.A), the liquid phase is treated in waste water treatment plants (included in 5.D.1). So the reporting, would also lead to a double-counting of emissions. For this reason only emissions from the digestion of manure and energy crops are reported, using the EMEP/EEA default emission factor.


Emissions were estimated using a simple methodology based on EMEP/EEA Guidebook. Two different fractions were considered: mixed waste treated in Mechanical-Biological Treatment (MBT) plants, covering waste from

households and similar sources covered by the municipal waste collecting system, but also significant amounts of waste from waste water treatment (e.g. sewage sludge) or smaller amounts of waste from industrial sources (e.g. residues from processing of recovered paper) are included.

biogenic waste composted, comprising green/biogenic waste collected and treated in com-posting plants (centralised composting) and biogenic waste composted at the place it is gen-erated (home composting).

Manure and energy crops digested in biogas plants (anaerobic digestion)

NH3 emissions for MBT, composting and anaerobic digestion were calculated by multiplying an emission factor with the quantity of waste.

NH3 Emissions = Mi * EFi Where:

Mi mass of organic waste treated by biological treatment type i (composting, MBT) EFi emission factor for treatment i (MBT, composting)

Methodological issues concerning anaerobic treatment plants using agricultural feedstock are explained within the appropriate chapter on sector 3 Agriculture (see Chapter 5.3.4).

Activity data

Historical activity data were taken from national publications and regional sources as listed in Table 294.

Since 2008, the ‘Electronic Data Management’ (EDM) is the primary data basis154, providing da-ta for the ‘Federal Waste Management Plan’ ‘BAWP’ (BMLFUW 2011, BMNT 2017), which is (in part) updated annually (‘Status Reports’ 2012, 2013, 2014, 2015; 2018). For years where no re-liable data are available inter- or extrapolation is applied.

154 In subcategory 5.A Solid Waste Disposal waste amounts have been taken from EDM reports already since 2008.



The EDM is an information network operated by the Umweltbundesamt. It is a central eGov-ernment initiative by the Austrian Federal Ministry of Climate Action, Environment, Energy, Mo-bility, Innovation and Technology (http://www.edm.gv.at) enabling enterprises, waste collectors and conditioners as well as authorities to handle registration, notification and reporting obliga-tions in the waste and environment sectors online. Waste amounts collected and treated (input-output records) have to be reported on an annual basis via this electronic tool.

Home composted amounts are calculated based on a per-capita value of 215 kg/person/a, whereas for Vienna only 15% of the population is considered due to the lower number of gar-dens in this urban area. This approach is in line with the method applied for the BAWP (BMNT 2017).

Mechanical-biologically treated waste for most recent years is taken directly from the EDM.

The EDM is also the main data source of biogenic waste treated in composting plants. Re-search by waste experts at the Umweltbundesamt indicates higher amounts of waste being composted than covered by the EDM due to some minor exemptions in the EDM reporting re-quirements and in some cases missing reports. Based on a study conducted in 2015 on munici-pal green waste (UMWELTBUNDESAMT 2016b), it is assumed that in 2011 10% of waste volumes reported are additionally composted, whereas this additional share is expected to decrease lin-early to 5% in 2014 as it is expected that reporting irregularities will further decrease. The 5% assumption is continued from 2015 and onwards as still reporting irregularities are expected.

Table 304: Activity data for NFR Category 5.B Composting.

Total waste

Mechanical-Biological Treatment

(MBT)

Composting Anaerobic treatment

Composting plants Home composting

[kt] [kt] Data source [kt] Data source

[kt] Data source [kt] Data source

1990 763 345

BAUMELER et al 1998

48

sum

of d

ata

repo

rted

by th

e A

ustri

an

Fede

ral P

rovi

nces

, (A

MLI

NG

ER

200

3) 370

AM

LIN

GE

R 2

003

0

Act

ivity

not

occ

urrin

g

1991 798 345 78 375 0 1992 942 345 137 460 0 1993 1 161 345 306 510 0 1994 1 373 345 444 585 0 1995 1 446 295 ANGERER 1997 551 600 0 1996 1 515 281 interpolated 617 616 0

1997 1 488 244 UMWELT-BUNDESAMT 1998b 582 663 0

1998 1 541 240 UMWELT-BUNDESAMT 2000c 604 696 0

1999 1 621 266 UMWELT-BUNDESAMT 2001d 623 732 0

2000 1 721 254 Interpolated

695

inte

rpol

ated

772 AMLINGER et al 2005 0

2001 1 953 242 767 944 interpolated

0 2002 2 186 230 834 1 117 5

intra

pola

ted

base

d on

EJ

by U

mw

eltb

unde

sam

t (2

015)

2003 2 418 218

BMLFUW 2008a

871 1 290 39 2004 2 932 488 899 1 462 calculated

based on BMLFUW 2008a

83 2005 3 150 623 903 1 472 152

2006 3 266 660 874 1 480 252

2007 3 367 684 884 1 485 BMLFUW 2008a 314

2008 3 387 619 interpolated 919 1 498 BMLFUW 2011

350 2009 3 401 555 EDM 977 1 505 364

http://www.edm.gv.at/



2010 3 452 551 1 035 1 488

calculated on basis of BMLFUW 2011

378 2011 3 495 519 1 118

EDM + EJ UMWELTBUNDESAMT (2015)

1 491 367

EDM

2012 3 573 453 1 239 1 496 385 2013 3 416 379 1 168 1 502 367 2014 3 538 413 1 215 1 511 399 2015 3 596 439 1 194 1 524 438 2016 3 728 442 1 300 1 540 447 2017 3 708 414 1 303 1 548 443 2018 3 747 412 1 294 1 554 486

Activity data on agricultural feedstock treated in anaerobic plants is provided within NFR sector 3 Agriculture (please refer to Table 265).

Emission factors

Due to different emission factors in different national references an average value was used for each of the two fractions of bio-technically treated waste.

Table 305: Emission factors for NFR Category 5.B.1 Composting.

NH3 [kg/t FS] References

Mechanical-biologically treated waste 0.6 (UMWELTBUNDESAMT BERLIN 1999) (AMLINGER et al. 2003, 2005) (ANGERER & FRÖHLICH 2002) (DOEDENS et al. 1999)

Composted waste (bio-waste, gardening waste, home composting)

0.4 (AMLINGER et al. 2003, 2005)

The NH3-emission factor for anaerobic treatment plants (NFR category 5.B.2) using agricultural feedstock is taken from the EMEP/EEA Guidebook 2019 (0.0275 kg NH3-N/ kg N according to Table 3.1). Details are provided in the chapter 5.3.4 in sector agriculture.


NH3 emissions from 5.B.2 anaerobic digestion were recalculated for the whole time series (-20.9 t in 2017) as the default emission factor for NH3-N was adapted according to the new EMEP/EEA Guidebook 2019.

For 5.B.1 Composting no recalculations were conducted.



6.5 NFR 5.C Incineration and open burning of waste

6.5.1 Source Description

In this category emissions are included from incineration of corpses (NFR 5.C.1.b.5), hospital waste (NFR 5.C.1.b.3), waste oil (NFR 5.C.1.b.i), incineration of domestic or municipal solid waste without energy recovery (NFR 5.C.1.a).

Additionally heavy metal and POPs emissions of a single plant without emission control 1990 to 1991 are included here. From 1992 the plant was equipped with ESP. Emissions 1992 to 2000 are included in category 1.A.1.a. Emissions from incineration of carcasses are not estimated. Waste incineration plants are allocated to category 1.A.4.a if heat is recovered for own usage but not used for generation of public electricity or heat or if the plant operator claims that the main economic activity (NACE code 38) of the plant is treatment of waste rather than the pro-duction of heat or electricity. This approach is consistent with national energy statistics.

In Austria waste oil is incinerated in especially designed so called “USK-facilities“ (Umweltschutz-komponenten). The emissions of waste oil combustion for energy use (e.g. in cement industry) are reported under NFR sector 1.A Fuel Combustion.

In general, municipal, industrial and hazardous waste are combusted in district heating plants or in industrial sites and the energy is used. Therefore their emissions are reported in NFR category 1.A Fuel Combustion. There is only one waste incineration plant which has been operated until 1991 with a capacity of 22 000 tons of waste per year without energy recovery and emission con-trols. This plant has been rebuilt as a district heating plant starting operation in 1996. Therefore the emissions of this plant are reported under NFR category 1.A Fuel Combustion from 1996 onwards. Small scale waste burning

Emissions from wood waste are considered in categories 3.F. It is assumed that other (illegal) small scale residential combustion occurs in heatings or stoves (included in category 1.A.4). Especially when considering POPs emissions from this source the national emission factors consider this issue due to the fact that POP emission factors are derived from field measure-ments which consider the “memory effect” of illegal waste co-incineration. Residential biomass heatings are widely used in Austria and wood use is based on a bottom up model by using household census data. It is assumed that illegal waste incineration just replaces other solid fuels and therefore other pollutants such as TSP, heavy metals and NOx from wood waste are also expected to be included in category 1.A.4.

Open burning of waste

Incineration of non-biogenic materials (e.g. waste tyres, rubber, plastics, paints, treaded wood…) outside of facilities is banned by federal legislation (Bundesgesetz über das Verbrennen von Materialien außerhalb von Anlagen (Bundesluftreinhaltegesetz – BLRG)).

6.5.2 Methodology

A tier 2 methodology is used. Emission factors are specific to type of waste and combustion technology.



Activity data

For municipal solid waste the capacity (22 000 tons of waste per year) of one operating waste incineration plant without energy recovery was used.

Waste oil activity data 1990 to 1999 were taken from (UMWELTBUNDESAMT 1995). For 2000 to 2005 the activity data of 1999 was used. (UMWELTBUNDESAMT 2001b) quotes that in 2001 total waste oil accumulation was about 37 500 t. Nevertheless, waste oil is mainly used for energy re-covery in cement kilns or public power plants and it is consequently accounted for in the energy balance as Industrial Waste.

Activity data of clinical waste is determined by data interpretation of the waste flow database at the Umweltbundesamt considering the waste key number “971” (“Abfälle aus dem medi-zinischen Bereich”) for the years 1990 and 1994 and extrapolated for the remaining time series.

Since 2005 the Austrian waste incineration regulation gives strong limits for air pollution for all kind of waste incineration without any limit of quantity. Since then all operators which do have an allowance for incineration of a specific type of waste needs to be registered in a federal da-tabase. The number of waste incineration plants which are not considered under sector 1.A is: Waste oil: 8 Clinical waste: 1 Municipal solid waste: None

The average yearly quantity of each waste incineration plant has been estimated as 500 t for hazardous clinical waste (plastics only). For waste oil the maximum USK facility capacity of 60.8 t per year (UMWELTBUNDESAMT 2001b) has been selected as activity data for each facility operat-ing in 2010 which leads to a rounded value of 500 tons/year. Activity data for the years 2006–2009 has been interpolated.

Activity data for cremation (number of corpses) is derived from the number of deceases as year-ly published by STATISTIK AUSTRIA. The number of cremations is derived from an analysis of in-formation as published by a Viennese, market dominating, funeral company about the percent-age of cremation of total funerals. The percentage increases from 12%155 in 1990 (about 10 k of incinerations) to 24% in 2004 and to 35% in 2011. The percentage 2012–2017 has been linearly interpolated to 44% in 2017 (about 37k incinerations), following a general trend in Austria which has been reported by market dominating funeral companies of larger cities.

Table 306: Activity data for IPCC Category 5.C Waste Incineration.

Year Municipal Waste [t]

Industrial waste [t]

Sewage sludge [t]

Clinical Waste [t]

Waste Oil [t]

1990 22 000 70 720 61 651 9 000 2 200

1991 22 000 70 720 61 651 7 525 1 500

1992 NO NO NO 6 050 1 800

1993 NO NO NO 4 575 2 100

1994 NO NO NO 3 100 2 500

1995 NO NO NO 3 100 2 600

1996 NO NO NO 3 100 2 700

1997 NO NO NO 3 100 2 800

1998 NO NO NO 3 100 2 900

1999–2005 NO NO NO 3 100 3 000

155 Estimate from (HÜBNER 2001b)



Year Municipal Waste [t]

Industrial waste [t]

Sewage sludge [t]

Clinical Waste [t]

Waste Oil [t]

2006 NO NO NO 2 500 2 500

2007 NO NO NO 2 000 2 000

2008 NO NO NO 1 500 1 500

2009 NO NO NO 1 000 1 000

2010–2018 NO NO NO 500 500

Emission factors

Heavy metal emission factors are taken from (HÜBNER 2001a). POPs emission factors are taken from (HÜBNER 2001b). Main pollutant emission factors: For municipal waste the industrial waste emissions factors from (BMWA 1990) are taken and converted by means of a NCV of 8.7 TJ/kt. Waste oil emission factors are selected similar to uncontrolled industrial residual fuel oil boilers. Clinical waste emission factors selected by means of industrial waste emissions factors from (BMWA 1990). Table 297 shows emission factors of main pollutants.

Table 307: NFR 5.C Waste Incineration: emission factors for main pollutants by type of waste.

Type of waste NOx CO NMVOC SO2 NH3

Waste oil [g/t] 8 060.0 604.5 403.0 18 135.0 110.0

Municipal waste [g/t] 870.0 1 740.0 330.6 1 131.0 0.2

Clinical waste [g/t] 7 000.0 840.0 330.0 700.0 0.2

Cremation [g/corps] 300.0 430.0 32.0 - -

Table 308: NFR 5.C Waste Incineration: emission factors for PM by type of waste.

Type of waste TSP PM10 PM2.5

Waste oil [g/t] 10.00 7.00 4.00

Municipal waste [g/t] IE(1) IE(1) IE(1)

Industrial waste [g/t] 28.00 25.00 21.00

Clinical waste [g/t] 10.00 7.00 4.00

Cremation [g/corps] 14.60 13.14 11.68 (1) PM emissions for MSW are included in NFR category 1.A.1.a.

Table 309: NFR 5.C. Waste incineration: emission factors for heavy metals and POPs.

Municipal waste

Cd Hg Pb PAH DIOX HCB [mg/t] [µg/t]

1990 71.0 299.0 1 170.0 0.7 250.0 850.0

1991 59.2 263.2 966.0 0.7 250.0 850.0



Industrial Waste


1990 510.0 112.0 2 400.0 1.6 160.0 970.0

1991 414.0 99.4 1 922.0 1.6 160.0 970.0

Sludges from waste water treatment


1990 235.0 55.0 730.0 1.6 1.5 300.0

1991 191.8 45.8 585.2 1.6 1.5 300.0

Clinical waste Cd Hg Pb PAH DIOX HCB [mg/t] [µg/t]

1990 4.77 5.76 540.00 0.00 1.08 216.00

1991 3.99 4.82 451.50 0.00 0.68 135.45

1992 3.21 3.87 363.00 0.00 0.36 72.60

1993 2.42 2.93 274.50 0.00 0.14 27.45

1994 1.64 1.98 186.00 0.00 0.00 0.19

1995–2005 0.62 0.71 7.75 0.00 0.00 0.19

2006 0.50 0.58 6.25 0.00 0.00 0.16

2007 0.40 0.46 5.00 0.00 0.00 0.12

2008 0.30 0.35 3.75 0.00 0.00 0.09

2009 0.20 0.23 2.50 0.00 0.00 0.06

2010–2018 0.10 0.12 1.25 0.00 0.00 0.03

Waste oil Cd Hg Pb PAH DIOX HCB [mg/t] [µg/t]

1990

360.0 30.0

106 300.0

6.7

17.0 17 020.0

1991 87 560.0 0.4 370.0

1992 68 820.0

1993 50 080.0

1994 31 340.0

1995–2018 13.0 60.0



Table 310: NFR 5.C.1.b.v cremation of corpses: emission factors.

SO2 Cd Hg Pb PAH Dioxin HCB PCB [mg/corps] [µg/corps]

113(8) 5.03(8) 3 000(4) 0.02(1) 0.40(1) 16.60(2) 3 320(2) 410(8)

2 500(5) 8.30(3) 1 660(3)

2 000(6)

1 000(7) 0(1)for all years (2) for 1990–1992 (3) for 1993–2017 (4) for 1990 (5) for 1991 (6) for 1992–1995 (7) for 2000–2018 (8) EMEP/EEA Guidebook 2019


Following a recommendation of the NECD 2019 review, SO2, Cd, and PCB emissions from 5.C.1.b.v cremation have been estimated by means of the tier 1 method from the EMEP/EEA Guidebook 2019.

6.6 NFR 5.D Wastewater handling


In this category NMVOC emissions from domestic wastewater handling (5.D.1) are included, covering wastewater of domestic origin – treated in municipal wastewater treatment plants, do-mestic wastewater treatment plants and cesspools – as well as commercial and industrial wastewater treated together with domestic wastewater in municipal wastewater treatment plants.


Emissions were calculated following the Tier 1 approach by multiplying the wastewater amounts with the emission factor taken from the EMEP/EEA 2019 Guidebook (15 mg/m3 wastewater). NMVOC Emissions = AD * EF

Where: AD activity data / volume of total wastewater treated in municipal wastewater treatment plants (m3) EF emission factor

Activity data

The activity data used to calculate NMVOC emissions consider only the waste water volumes treated in municipal wastewater treatment plants, and exclude wastewater treated in individ-ual septic systems (as recommended by the ERT in 2017). Therefore the domestic wastewater volumes are deducted from the total municipal waste water volumes.



Waste water volumes treated in municipal wastewater treatment plants are collected in the Electronic Emission Register of Surface Water Bodies (“Emissionsregister – Oberflächen-wasserkörper”, abbreviated “EMREG-OW”156), an electronic register of material emissions to surface water bodies from point sources, especially municipal sewage treatment plants. It is administered by the Ministry for Climate Action, Environment, Energy, Mobility, Innovation and Technology (BMK)157 and serves the collection of information for the National Water Manage-ment Plan and for management plans for international river catchment areas.

Wastewater volumes treated in municipal wastewater treatment plants for the years 2010 to 2018 are retrieved from this emission register and used in the inventory. For 2009 interpolation was carried out.

Data for 2006–2008 were taken from the Austrian sewage sludge database administered by the Umweltbundesamt. Historical data (1991, 1995, 1998, 2001, 2003) were obtained from the Wa-ter Quality Reports (BMLFUW 1993–2002); data in between were interpolated.

Data on volumes of wastewater collected in domestic wastewater treatment plants and cess-pools are calculated based on the Austrian population not connected to municipal wastewater treatment plants and the factor 135 litre per population equivalent per day (ÖWAV 2015). Data on wastewater disposal routes and connection rates were taken from the situation reports on municipal wastewater (BMLFUW 2006C, BMLFUW 2008b, BMLFUW 2010, BMLFUW 2012, BMLFUW 2014a, BMLFUW 2016, BMNT 2018C). For 2018 preliminary data had to be used as information on the connection rate in some federal provinces were missing at the time of inventory compilation (Umweltbundesamt 2020b).

Concerning the latrine use, Austria has ensured that all households have proper wastewater treatment, either smaller wastewater treatment plants, individual sewage treatment or septic tanks (BMLFUW 2016). Latrines are therefore not used in Austria, and if, it is to a negligible ex-tent.

Table 311: Activity data for 5.D Wastewater handling.

Year Total waste water volumes [m3]

Domestic wastewater treatment [m3]

Wastewater treated in municipal WWTP [m3]

1990 811 786 584 172 213 666 639 572 918

1991 819 806 717 169 699 210 650 107 507

1992 827 826 850 157 100 332 670 726 519

1993 835 846 983 143 804 467 692 042 516

1994 843 867 116 129 706 029 714 161 087

1995 851 887 250 115 229 335 736 657 915

1996 927 538 166 104 644 768 822 893 398

1997 1 003 189 083 94 011 010 909 178 073

1998 1 078 840 000 83 350 000 995 490 000

1999 1 075 226 667 79 566 667 995 660 000

2000 1 071 613 333 75 783 333 995 830 000

2001 1 068 000 000 72 000 000 996 000 000

156 BGBl. II Nr. 29/2009: Verordnung des Bundesministers für Land- und Forstwirtschaft, Umwelt und Wasserwirtschaft

über ein elektronisches Register zur Erfassung aller wesentlichen Belastungen von Oberflächenwasserkörpern durch Emissionen von Stoffen aus Punktquellen (EmRegV-OW)

157 (the former Federal Ministry of Sustainability and Tourism (BMNT) respectively former Austrian Federal Ministry of Agriculture, Forestry, Environment and Water Management (BMLFUW)



Year Total waste water volumes [m3]

Domestic wastewater treatment [m3]

Wastewater treated in municipal WWTP [m3]

2002 1 064 500 000 64 388 229 1 000 111 771

2003 1 061 000 000 56 776 457 1 004 223 543

2004 1 070 201 502 49 164 686 1 021 036 816

2005 1 079 403 004 41 552 914 1 037 850 090

2006 1 088 604 506 33 941 143 1 054 663 363

2007 1 110 000 339 34 021 586 1 075 978 754

2008 1 091 435 720 30 054 497 1 061 381 223

2009 1 114 220 585 27 735 147 1 086 485 437

2010 1 137 005 449 25 415 798 1 111 589 652

2011 1 020 826 719 24 160 697 996 666 022

2012 1 081 559 943 22 905 597 1 058 654 346

2013 1 187 433 343 22 091 808 1 165 341 536

2014 1 131 070 586 21 278 018 1 109 792 568

2015 1 060 093 444 20 974 704 1 039 118 740

2016 1 135 233 391 20 671 389 1 114 562 002

2017 1 093 098 753 20 585 418 1 072 513 335

2018 1 070 896 259 20 467 467 1 050 428 792

In the year 2018158 95.3% of the Austrian population is connected to municipal wastewater treatment plants. The remaining wastewater is treated either in septic tanks (2.9%), domestic wastewater handling systems (1.6%), or disposed otherwise (‘unspecified disposal routes’: 0.2%).


For NMVOC from category 5.D.1 domestic wastewater a recalculation for 2017 was carried out (from 16.82 t to 16.09 t) as new data on wastewater volumes became available. This new data was used to replace activity data that had been extrapolated based on population growth.

6.7 NFR 5.E Other Waste


In this category TSP, PM10, PM2.5, Pb, Cd, Hg and PCDD/F emissions from unwanted fires in cars and various types of houses (industrial buildings, detached houses and apartments) are in-cluded. Following the EMEP/EEA guidelines a Tier 2 methodology was applied, using country specific activity data and the given default values.

158 the latest year for which data on connection rate is currently available




Emissions were calculated following the Tier 2 approach by multiplying the number of fires per category with the emission factor taken from the EMEP/EEA 2019 Guidebook. Emissions = AD * EF

Where: AD activity data (number of fires) EF emission factor

Activity data

The activity data for car fires are from a national fire statistic and include car and truck fires for the years 1996 until 2011, as well as 2015, 2016 2017 (ÖBFV 2017) and 2018. For the years were data is missing, a mean value of car fires by 1000 inhabitants from the available years was applied to the total number of inhabitants.

The determination of the building fires required an estimate of the number of buildings in the various types of houses.

There are national statistics for Industry, Business (called “Gewerbe” in Austria) and Civil fires available from 2005 onwards. From 1990 to 2005, the number of industrial building fires was de-rived as the mean values of fires during the years 2005 until 2015. The number of civil fires dur-ing 1990-2005 was extrapolated based on the mean value of fires during 2005-2010 per inhab-itant.

As only a share of the total civil fires can be attributed to detached houses and apartments, a split is necessary. The split into the different building types for the residential sector is based on a detailed fire indemnity statistics of a representative Austrian province, available for the years 2010 and 2015. Of the categories used in the EMEP/EEA Guidebook 2016, values are available for detached, apartments and industrial buildings; undetached houses are included in the de-tached category. This is the same approach as used by Slovakia. The building stock in Slovakia is similar to Austria – traditionally in Austria exist only very few undetached houses.

For the years 2005 to 2018 data on national fire statistics are available for civil and industrial buildings (BV 2015, BV 2018).. For 1990 to 2004 the number of fires were determined based on the mean value of fire accidents per inhabitant 2005-2010 and the population numbers 1990-2004.

Table 312: Activity data for 5.E Other Waste- accidental fires.

Year Car fires Industrial building fires

Detached house fires

Apartment fires

1990 1 586 1 373 935 687

1991 1 602 1 373 944 694

1992 1 620 1 373 955 702

1993 1 633 1 373 963 708

1994 1 639 1 373 966 710

1995 1 642 1 373 968 711

1996 1 437 1 373 969 712

1997 1 379 1 373 970 713

1998 1 510 1 373 971 714

1999 1 584 1 373 973 715



Year Car fires Industrial building fires

Detached house fires

Apartment fires

2000 1 682 1 373 976 717

2001 1 619 1 373 979 720

2002 1 900 1 373 984 723

2003 1 868 1 373 989 727

2004 1 844 1 373 995 731

2005 1 759 1 161 839 617

2006 1 753 1 193 820 603

2007 1 869 1 401 1 072 788

2008 1 552 1 327 1 050 772

2009 1 485 1 401 1 028 756

2010 1 727 1 358 1 261 927

2011 1 733 1 411 1 201 883

2012 1 741 1 524 1 212 891

2013 1 751 1 266 1 045 768

2014 1 765 1 488 1 224 900

2015 1 584 1 574 1 210 890

2016 2 266 1 334 1 135 834

2017 1 540 1 462 1 141 839

2018 1 552 1 186 943 693

Emission Factors

The following emission factors have been used, which are the Tier 2 default values as present-ed in the EMEP/EEA Guidebook 2019.

Information on the condensable component to be included or excluded in the applied PM emis-sion factors can be found in chapter 12.3.



Table 313: Emission factors for unwanted fires.

Year EF for car fires EF for detached houses

EF for industrial buildings

EF for apartments

TSP 2.3 kg/fire 143.82 kg/fire 27.23 kg/fire 43.78 kg/fire

PM10 2.3 kg/fire 143.82 kg/fire 27.23 kg/fire 43.78 kg/fire

PM2.5 2.3 kg /fire 143.82 kg/fire 27.23 kg/fire 43.78 kg/fire

PCDD/F 0.048 mg/fire 1.44 mg/fire 0.27 mg/fire 0.44 mg/fire

Pb NE 0.42 g/fire 0.08 g/fire 0.13 g/fire

Cd NE 0.85 g/fire 0.16 g/fire 0.26 g/fire

Hg NE 0.85 g/fire 0.16 g/fire 0.26 g/fire


Minor recalculations for 2017 from category 5.E other waste were due to activity data becoming availa-ble (data on building fires 2017) resulting in an increase of 1,9% in 2017 for TSP/PM10/PM2.5, Pb, Cd, Hg and PCDD/F.

Austria’s Informative Inventory Report (IIR) 2020 – Recalculations and Improvements


7 RECALCULATIONS AND IMPROVEMENTS

7.1 Relation to data reported earlier

As a result of the continuous improvement of Austria’s National Air Emission Inventory, emis-sions of some sources have been recalculated based on updated data or revised methodolo-gies, thus emission data for 1990 to 2017 submitted this year might differ from data reported pre-viously.

CLRTAP Review

The Stage 1 review (initial check of submissions for timeliness, completeness and formats) and Stage 2 review (check of consistency, comparability, KCA, trends and IEFs) are carried out an-nually. Stage 3 or so-called In-depth reviews take place for selected inventories as in the work plan approved by the EMEP Steering Body159. The last In-depth (Stage 3) review of the Austrian Inventory took place in 2017 (UNITED NATIONS 2017); the findings are summarised in Table 319. The next Stage 3 review is currently not scheduled, but will be within the next five years. NEC Review

From 2017 onwards the national emission inventory data will be also checked by the European Commission as set out in Article 10 of Directive 2016/2284 (NEC Directive). The inventories are checked annually in order to verify the transparency, accuracy, consistency, comparability and completeness of information submitted and to identify possible inconsistencies with the re-quirements set out under international law, in particular under the LRTAP Convention. Syner-gies are maximised with the 'Stage 3' reviews conducted by the LRTAP Convention.The find-ings under the NEC Review 2019 for Austria are summarised and commented in Table 320.

The figures presented in this report replace data reported earlier by the Umweltbundesamt un-der the reporting framework of the UNECE/LRTAP Convention and NEC Directive of the Euro-pean Union.

7.2 Explanations and Justifications for Recalculations, including in response to the review process

Explanations for recalculations per sector are given in the respective chapters, the tables indi-cating the recalculations can be found in the Chapter 7.3.

Compiling an emission inventory includes data collecting, data transfer and data processing. Data has to be collected from different sources, for instance national statistics, associations, plant operators, studies, personal information, other publications.

159 http://www.ceip.at/ms/ceip_home1/ceip_home/review_process/stage3_review_ae/

http://www.ceip.at/ms/ceip_home1/ceip_home/review_process/stage3_review_ae/





The provided data must be transferred from different data formats and units into a unique elec-tronic format to be processed further. The calculation of emissions by applying methodologies on the collected data and the final computing of time series into a predefined format (NFR) are fur-ther steps in the preparation of the final submission. Finally the submission must be delivered in due time. Even though a QA/QC system gives assistance so that potential error sources are avoided as far as possible it is necessary to make some revisions – so called recalculations – under the following circumstances: An emission source was not considered in the previous inventory. A source/data supplier has delivered new data because previous data were preliminary data

only (by estimation, extrapolation) or the methodology has been improved. Occurrence of errors in data transfer or processing: wrong data, unit-conversion, software er-

rors etc. Methodological changes: a new methodology must be applied to fulfil the reporting require-

ments because one of the following reasons: to decrease uncertainties; an emission source becomes a key source; consistent input data needed for applying the methodology is no longer accessible; input data for more detailed methodology is now available; the methodology is no longer appropriate.

The following sections describe the methodological changes made to the inventory since the previous submission (for each sector).

7.2.1 Energy (1)

7.2.1.1 Revision of the energy balance

The federal office for national statistics, “Statistik Austria”, revised the energy balance for the years 1990 to 2017 with the following main implications for energy consumption as used in the inventory: Natural gas gross inland consumption 2014 and 2015 has been revised downwards by -1 and

-1.8 TJ. Moreover, natural gas consumption has been shifted to different sectors: For 2005 and 2006, about 1 to 1.2 PJ have been shifted from the power sector (1.A.1.a) to the com-mercial sector (1.A.4.a). For 2011, about 0.7 PJ have been shifted from the power sector (1.A.1.a) to the commercial sector (1.A.4.a). For 2013, about 1.7 PJ have been shifted from the commercial and residential sector (1.A.4.a and 1.A.4.b) to the industry sector (1.A.2). For 2014, about 1.1 PJ have been shifted from the residential and commercial sector (1.A.4.a and 1.A.4.b) to the industrial sector (1.A.2). For 2016, about 3 PJ have been shifted from pe-troleum refineries (1A1b) to the residential and industry sector (1.A.4.b, 1.A.2).

For liquid fuels, gross inland consumption has been revised downwards by - 0.1 to -2.2 PJ for the years 2005 to 2011 (crude oil input into refineries) and by - 1.3 PJ PJ for the year 2017, which does not have an effect on final consumption, because lower fuel imports have been counterbalanced by higher refinery fuel output. For the period 2013 to 2017, between 1.1 and 4.6 PJ of liquid fuels have been shifted from the industry sector (mostly from 1.A.2.e food processing and 1.A.2.g other manufacturing industries) to the residential (1.A.4.b) and com-mercial (1.A.4.a) sector.

For solid fuels, mainly the residential sector has been revised for the years since 2005 (+ 1 PJ in 2005 and + 0.2 PJ in 2017).



For ‘biomass’, gross inland consumption has been revised upwards for the whole time series 2005 – 2017 (2005: + 7 PJ, 2010: + 15.7 PJ, 2015: 9.4 PJ, 2017: + 14.5 PJ). For the years 2005 to 2016, transformation input to the power sector (1.A.1.a) has been revised downwards (by - 0.4 to - 2.7 PJ) while for 2017 it has been revised upwards by + 3.5 PJ, which explains most of the higher NOX (+7%) and PM2.5 (+6%) emissions in 2017 of category 1.A.1.a. The largest revision to biomass consumption took place in the 1.A.4 stationary combustion sub-categories, with increases of + 6.4 PJ in 2005 and + 12.6 PJ in 2017.

7.2.1.1 Stationary combustion 1.A.1.a, 1.A.1.b, 1.A.1.c, 1.A.2.a-1.A.2.g and 1.A.4.a-1.A.4.c

In general, recalculations follow the revisions of the energy balance. Revisions of methodologies are outlined in the following paragraphs:

7.2.1.2 Petroleum refining (1.A.1.b)

Cd emissions from 1.A.1.b refineries have been re-estimated using a method developed by CONCAWE (CONCAWE 2017). This results in higher Cd emissions 1990 but lower Cd emissions 2017.

7.2.1.3 Pulp and paper industry (1.A.2.d)

Based on a new study (Windsperger et al 2020) performed in 2019, NOx and PM2.5 emission factors from hard coal, black liqueur and wood waste used in pulp and paper industries have been revised, resulting in NOX emissions that are about - 0.8 kt lower and PM2.5 emissions that are slightly higher for 2017.

7.2.1.4 Chemicals industry (1.A.2.c)

NOx, SO2 and PM10 emissions from a large waste incineration plant are now based on meas-ured data. This results in NOx emissions from category 1.A.2.c that are about - 0.1 kt lower, SO2 emissions that are - 0.3 kt lower and PM2.5 emissions that are - 0.2 kt lower for the year 2017.

7.2.1.5 Other sectors (1.A.4.ai, 1.A.4.bi, 1.A.4.ci)

Changes according to a revision of the energy demand model for space heating

The module ‘Heating type by technology’ was updated with a new approach based on recent market data and expert consultation (on the sale of fuel technology). This information was used for remodelling the heating stock and turnover based on two studies, resulting in a revised con-sumption by type of heating.

Additionally, the mixed-fuel wood boiler stock was subdivided into two categories (advanced and conventional). Advanced technology is associated with (slightly) lower NOx, NMVOC and PM2.5 emissions than conventional equipment.

7.2.1.6 Road Transport (1.A.3.b)

The domestic activity data (fuel consumption/mileage) has been updated fundamentally with new specific mileage per vehicle category: for the first time, data from periodic roadworthiness testing has been evaluated resulting in new age-related mileage data and improved data accu-racy. This affects the categories passenger cars (PC), light-duty vehicles (LDV) and motorcycles (MC).



Update/Improvement of methodology and emission factors

By using the latest version of the emission model “NEMO” from the Graz University of Technol-ogy for emission calculations, the following improvements to the model and to the input data were obtained, resulting in emission changes as described below:

New specific mileage per vehicle category: for the first time, data from periodic roadworthi-ness testing has been evaluated resulting in new age-related mileage data. This affects the categories PC, LDV and MC. In the case of cars, the analysis of this new data source led to the following findings: Old vehicles are driven more than previously (and generally) assumed and The specific mileage per car for each year of a vehicle’s age is lower than previously as-

sumed These facts generally lead to a decrease in the total domestic mileage of passenger cars

over the entire time series. New and improved emissions factors for all vehicle categories: The most recent version of the emission calculation model NEMO (TU-Graz) includes the re-

cently released emission factor database HBEFA 4.1. All consumption factors were checked or revised within this new software version. The implementation of the new HBEFA Version 4.1 resulted in an increase in emission fac-tors for all vehicle categories. Due to dieselgate and the mandatory PEMS measurements for the Euro 6d_temp standard, large amounts of new measurement data have become availa-ble. New findings, such as the influence of ambient temperature on the functional efficiency of NOx exhaust after-treatment systems (such as SCR), new aging conditions of such sys-tems, new improved traffic situations combined with revised dynamic parameters, have led to an increase in the specific emissions for each vehicle category.

According to the bottom-up/top-down methodology applied for the calculation of domestic fuel consumption and fuel export, an increased use of domestic diesel always results in a reduction of the quantities handled in fuel export, and vice versa. As fuel export is mainly associated with truck traffic, the emission reduction or increase is strongly reflected in subsector 1.A.3.b.3 Heavy duty trucks and buses. 7.2.1.7 Coal mining and handling (1.B.1.a)

The recalculations of PM2.5 emissions in category 1.B.1.a (Coal Mining and Handling) for the years 2005–2017 are due to a revision of the energy balance by Statistik Austria. This revision has led to an increase by 0.0004 kt PM2.5 emissions in 2017.

7.2.1.1 Other fugitive emissions from energy production (Geothermal energy) (1.B.2.d)

Following a recommendation of the NECD 2019 review, NH3 emissions from category 1.B.2.d Other fugitive emissions from energy production (Geothermal energy) have been estimated for the first time.

7.2.2 Industrial Processes and Product Use (2)

7.2.2.1 Other chemical industry (2.B.10.a)

Due to a transcription error, the NMVOC emissions of one chemical plant had to be revised for the whole time series (+ 0.008 kt NMVOC in 2017)



7.2.2.2 Iron and Steel Production (2.C.1)

In this year’s submission estimates for the PAH fractions BAP, BBF, BKF, IND category 2.C.1 has been included for the first time.

7.2.2.3 Solvent Use (2.D.3)

Following in-depth QC activities, time series inconsistencies in the solvents model were re-moved: (i) the reporting categories of the import/export statistics for various ethers had changed over time and have now been considered consistently; and (ii) for antifreeze fluids, of which not all reported in the category are relevant for VOC emissions, the same assumption as the one used in the years before has been applied. This has led to a decrease in activity data (Solvents Used), leading to a decrease in emissions. Hg emissions

Due to the omission of the EF for Hg from the EMEP EEA GB 2019, this source is no longer re-ported.

7.2.2.4 Other product use (2.G)

More detailed statistical data became available on cigarettes sold in Austria, as well as loose tobacco and cigars taxed in Austria from 1997 onwards. The trend was then extrapolated back to 1990. This led to an increase of emissions of NOx, CO, NMVOC, NH3, TSP, PM10, PM2.5, Cd, Ni, Zn, Cu, Dixon and PAHs.

7.2.2.5 2.H Other processes (2.H)

In this year’s submission an estimate of the PAH fractions BAP, BBF, BKF, IND in Sector 2.H.2 has been included for the first time.

7.2.2.6 Wood processing (2.I)

Due to recalculations of the energy balances, the activity data had to be updated. Thus, particu-lar matter emissions since 2005 have changed (- 0.001 kt PM2.5 for 2017).

7.2.3 Agriculture (3)

7.2.3.1 Manure Management (3.B)


Livestock numbers of poultry and other animals (mainly deer) have been revised as new data has become available based on the final results of the farm structure survey 2016 (STATISTIK AUSTRIA 1990-2019). To avoid jumps in the time series, the years 2014 and 2015 have been in-terpolated. As currently no updated data is available for the respective livestock categories, the values of 2016 have been used for the years 2017 and 2018. Manure Management (3.B) – NH3

The main reason for revised NH3 emissions from manure management is the implementation of the new EMEP/EEA Guidebook 2019 (EEA 2019) in Austria’s air emission inventory. The 2019 version of the Guidebook provides updated NH3 emission factors for housing and storage for



the livestock categories layers, broilers, sheep and other animals. Furthermore, the calculation method, which is based on the fraction of TAN that is immobilised in organic matter (fimm) when the manure is managed as a litter-based solid and the litter is straw, has been revised. Accord-ing to (EEA 2019), this immobilisation greatly reduces the potential NH3-N emission during stor-age and after application.

The improved calculations resulted in lower NH3 emissions from manure management for the whole time series (– 1.4 kt NH3 in 2017)

Biological treatment of waste (5.B.2) – NH3

NH3 emissions from anaerobic digestion at biogas facilities are calculated in sector 3 Agriculture but reported under sector 5 Waste. The Tier 1 methodology of the EMEP/EEA Guidebook is applied. In the EMEP/EEA GB 2019 the NH3-N EF was changed from 0.0286 kg of NH3-N to 0.0275 kg of NH3-N, leading to a downward revision across the whole time series (– 0.02 kt NH3 in 2017).

Manure Management (3.B) – NOx

NOx emissions are calculated using a mass-flow approach based on the concept of a flow of TAN through the manure management system according to the EMEP/EEA GB 2019. Although there were no changes in the methodology for NOx between the Guidebook versions 2016 and 2019, the revisions in the ammonia inventory had an impact on NOx and resulted in lower emis-sions for the whole time series (– 0.01 kt NOx in 2017).

Manure Management (3.B) – NMVOC

The NMVOC emission calculations according to the 2019 EMEP/EEA Tier 2 methodology are strongly linked to the compilation of the ammonia emissions inventory. Therefore, although there were no changes in the methodology for NMVOC between the Guidebook versions 2016 and 2019, the revisions to the ammonia inventory also had an impact on NMVOC emissions. The improved calculations resulted in recalculations for the whole time series (+ 0.09 kt NMVOC in 2017).

Manure Management (3.B) - Particle Emissions

Reasons for the recalculated emissions from 2014 to 2017 are the updated activity data of poul-try and other animals.

7.2.3.2 Agricultural Soils (3.D)


Livestock numbers of poultry and other animals (mainly deer) have been revised as new data has become available based on the final results of the farm structure survey 2016 (STATISTIK AUSTRIA 1990-2019, see Chapter 1.3.8)

Detailed raw material and energy balances (3.D.a.2.c) In 2019 new information on input materials for Austria’s biogas plants became available (E-CONTROL 2019) resulting in slightly revised amounts of digested manure and energy crops.



Methodological changes

Agricultural Soils (3.D) NH3

3.D.a.1 Inorganic N fertilisers Revised emissions from inorganic N fertilisers are due to the implementation of new information on agriculture practice. Including the rapid incorporation of urea into the soil in Austria’s calcula-tions resulted in lower NH3 emissions from synthetic fertiliser application for the entire time se-ries (– 0.6 kt NH3 in 2017).

3.D.a.2.a Animal manure applied to soils NH3 emissions of animal manure applied on soils have been revised downwards for the entire time series. The main reasons are updated NH3 emission factors for manure spreading for the livestock categories layers and broilers according to the EMEP/EEA GB 2019, as well as im-provements carried out in the manure management sector due to the new Guidebook (e.g. up-dated NH3 emission factors and an improved calculation of the immobilised fraction of TAN, see Chapter 6.3.2.1). These changes led to a downward revision of the NH3 emissions by – 1.3 kt for the year 2017.


According to the EMEP/EEA GB 2019, the default Tier 2 NH3 EFs for grazing for the livestock categories sheep and other animals have been revised downwards compared to the 2016 GB. This results in lower NH3 emissions for the whole time series (– 0.06 kt NH3 in 2017). Agricultural Soils (3.D) NOx

3.D.a.2.a Animal manure applied to soils The revisions to the ammonia calculations according to the EMEP/EEA GB 2019 in the manure management sector have led to higher N amounts available for application. As a consequence, NOx emissions of manure application have been resived upwards for the entire time series (+ 0.1 kt NOx in 2017).

Agricultural Soils (3.D) HCB

3.D.f. Use of Pesticides Following a recommendation of the NEC Review 2019 Austria estimated these emissions for the first time.

Agricultural Soils (3.D) NMVOC

3.D.a.2.a Animal manure applied to soils NMVOC emissions from manure application have been estimated based on the 2019 EMEP/EEA Tier 2 methodology which is closely linked to the compilation of the ammonia inven-tory. Therefore, the revisions to the ammonia inventory also had an impact on the NMVOC emissions and resulted in lower emissions for the entire time series (– 0.3 kt NMVOC in 2017).

7.2.3.3 Field burning of agricultural residues (3.F) – NOx, SO2, NMVOC, PM

The EMEP/EEA Tier 2 emission factors for orchard crops provided in the guidebook chapter 5.C.2 Small-scale waste burning were used for the first time resulting in revised emissions for NOx, SO2, NMVOC, CO, TSP, PM10, PM2.5, Cd, Pb, and PAHs.



7.2.4 Waste (5)

7.2.4.1 Waste disposal on land (5.A)

Minor recalculations of particulate matter emissions from waste disposal (- 2.5 t TSP, - 1.2 t PM10, - 0.4 t PM2.5 in 2017) were caused by the correction of a transcription error.

7.2.4.2 Biological Treatment (5.B)

NH3 emissions from anaerobic digestion at biogas facilities (5.B.2) are calculated in sector 3 Ag-riculture but reported under sector 5 Waste. The Tier 1 methodology of the EMEP/EEA Guide-book is applied. In the new EMEP/EEA GB 2019 the NH3-N EF was changed from 0.0286 kg of NH3-N to 0.0275 kg of NH3-N, leading to a downward revision across the whole time series (– 0.02 kt NH3 in 2017).

7.2.4.3 Incineration and open burning of waste (5.C)

Following a recommendation from the NECD 2019 review, SO2 emissions from 5.C.1.b.v crema-tion have been estimated the first time.

7.2.4.4 Wastewater (5.D)

For NMVOC from category 5.D.1 domestic wastewater a recalculation for 2017 was carried out (from 16.82 t to 16.09 t) as new data on wastewater volumes became available. This new data was used to replace activity data that had previously been extrapolated based on population growth.

7.2.4.5 Other waste (5.E)

Minor recalculations of particulate matter emissions for 2017 from category 5.E other waste (+4.6 t TSP/PM10/PM2.5) were made as activity data became available for this years’ submission (data on building fires 2017).

.



7.3 Recalculations per Pollutant

The following tables present the changes in emissions160 for all relevant pollutants compared to the previous submission (IIR 2019). Detailed explanations are provided in the sectoral chapters.

Table 314: Recalculation difference of SO2 emissions [kt] with respect to submission 2019.

1990 2017 Absolute Diff. SO2 emissions [kt] ∆% Subm.

2019 Subm. 2020

∆% Subm. 2019

Subm. 2020

1990 2017

1.A.1 Energy Industries 0.0% 14.06 14.07 3.4% 1.29 1.33 0.01 0.04


-0.4% 17.90 17.83 -2.9%

9.25 8.98 -0.07 -0.27

1.A.3 Transport 0.0% 5.13 5.13 1.0% 0.30 0.30 0.00 0.00

1.A.4 Other Sectors 0.0% 32.66 32.66 18.6% 1.35 1.60 0.00 0.25

1.A.5 Other = 0.01 0.01 = 0.02 0.02 - -

1.B Fugitive Emissions = 2.00 2.00 = 0.04 0.04 - -


= 1.93 1.93 = 0.57 0.57 - -

3 Agriculture 10.8% 0.00 0.01 39.7% 0.00 0.00 0.00 0.00

5 Waste 0.0% 0.07 0.07 43.6% 0.01 0.01 0.00 0.00

Total Emissions -0.1% 73.76 73.70 0.3% 12.81 12.84 -0.07 0.03

Table 315: Recalculation difference of NOx emissions [kt] with respect to submission 2019.

1990 2017 Absolute Diff. NOx emissions [kt] ∆% Subm.

2019 Subm. 2020

∆% Subm. 2019

Subm. 2020

1990 2017



0.0% 33.03 33.03 -4.0% 27.91 26.79 0.00 -1.12

1.A.3 Transport -2.2% 122.76 120.02 23.4% 74.23 91.57 -2.74 17.34

1.A.4 Other Sectors 1.8% 29.32 29.85 1.5% 19.97 20.26 0.52 0.29

1.A.5 Other = 0.07 0.07 = 0.08 0.08 - -

1.B Fugitive Emissions = IE IE = IE IE - -


0.0% 4.27 4.27 0.5% 0.47 0.47 0.00 0.00

3 Agriculture 0.5% 11.99 12.05 1.0% 10.88 10.99 0.06 0.11

5 Waste = 0.10 0.10 = 0.02 0.02 - -

Total Emissions -1.0% 219.33 217.22 11.9% 144.71 161.95 -2.11 17.24

160 An equals sign “=” in the field for relative difference indicates that reported emissions do not differ from the previous

submission; blank fields indicate that no such emissions occur from this sector;



Table 316: Recalculation difference of NMVOC emissions [kt] with respect to submission 2019.

1990 2017 Absolute Diff. NMVOC emissions [kt] ∆% Subm.

2019 Subm. 2020

∆% Subm. 2019

Subm. 2020

1990 2017

1.A.1 Energy Industries -4.7% 0.33 0.32 -12.7% 0.39 0.34 -0.02 -0.05


0.0% 1.68 1.68 0.0% 1.13 1.13 0.00 -0.00

1.A.3 Transport 10.5% 88.48 97.78 -33.4% 8.95 5.96 9.31 -2.99

1.A.4 Other Sectors 2.1% 46.86 47.85 0.1% 29.63 29.67 0.99 0.04

1.A.5 Other 0.0% 0.01 0.01 0.1% 0.02 0.02 0.00 0.00

1.B Fugitive Emissions = 15.49 15.49 = 2.29 2.29 - -


0.0% 118.53 118.54 -15.5% 40.19 33.96 0.01 -6.24

3 Agriculture -1.3% 52.87 52.19 -0.6% 37.53 37.31 -0.68 -0.22

5 Waste = 0.16 0.16 -1.2% 0.06 0.06 - -0.00

Total Emissions 3.0% 324.40 334.02 -7.9% 120.19 110.73 9.61 -9.46

Table 317: Recalculation difference of NH3 emissions [kt] with respect to submission 2019.

1990 2017 Absolute Diff. NH3 emissions [kt] ∆% Subm.

2019 Subm. 2020

∆% Subm. 2019

Subm. 2020

1990 2017



0.0% 0.33 0.33 -3.2% 0.39 0.38 0.00 -0.01

1.A.3 Transport -27.2% 1.10 0.80 -13.0% 1.29 1.12 -0.30 -0.17

1.A.4 Other Sectors 0.0% 0.63 0.63 12.2% 0.57 0.64 -0.00 0.07

1.A.5 Other = 0.00 0.00 = 0.00 0.00 - -

1.B Fugitive Emissions = IE IE NEW IE 0.00 IE 0.00


0.8% 0.34 0.34 3.1% 0.16 0.17 0.00 0.01

3 Agriculture -5.1% 62.23 59.06 -5.1% 64.62 61.30 -3.16 -3.32

5 Waste -0.1% 0.37 0.37 -1.3% 1.62 1.60 -0.00 -0.02

Total Emissions -5.3% 65.19 61.73 -5.0% 69.09 65.67 -3.46 -3.43

Table 318: Recalculation difference of CO emissions [kt] with respect to submission 2019.

1990 2017 Absolute Diff. CO emissions [kt] ∆% Subm.

2019 Subm. 2020

∆% Subm. 2019

Subm. 2020

1990 2017

1.A.1 Energy Industries 0.6% 6.07 6.10 -2.9% 4.72 4.59 0.03 -0.14


-0.1% 231.55 231.22 -0.8% 163.08 161.82 -0.33 -1.25

1.A.3 Transport 9.2% 491.97 537.13 -9.8% 79.50 71.69 45.16 -7.81

1.A.4 Other Sectors 6.0% 401.90 426.00 3.7% 263.39 273.03 24.10 9.64

1.A.5 Other = 0.22 0.22 = 0.30 0.30 - -

1.B Fugitive Emissions = IE IE = IE IE - -


0.1% 37.16 37.19 0.5% 14.08 14.14 0.03 0.07

3 Agriculture 2.0% 1.20 1.23 5.6% 0.34 0.35 0.02 0.02

5 Waste = 10.31 10.31 = 3.15 3.15 - -

Total Emissions 5.8% 1 180.39 1 249.41 0.1% 528.55 529.08 69.02 0.53



Table 319: Recalculation difference of Cd emissions [t] with respect to submission 2019.

1990 2017 Absolute Diff. Cd emissions [t] ∆% Subm.

2019 Subm. 2020

∆% Subm. 2019

Subm. 2020

1990 2017

1.A.1 Energy Industries 19.8% 0.27 0.33 -10.0% 0.32 0.28 0.05 -0.03


0.6% 0.31 0.31 7.4% 0.20 0.21 0.00 0.01

1.A.3 Transport -73.2% 0.06 0.02 -74.7% 0.11 0.03 -0.04 -0.08

1.A.4 Other Sectors -4.0% 0.42 0.40 18.8% 0.27 0.32 -0.02 0.05

1.A.5 Other = 0.00 0.00 0.0% 0.00 0.00 - 0.00

1.B Fugitive Emissions = NA NA = NA NA - -


0.5% 0.63 0.63 2.0% 0.32 0.33 0.00 0.01

3 Agriculture -8.4% 0.01 0.01 -27.6% 0.00 0.00 -0.00 -0.00

5 Waste 0.1% 0.06 0.06 10.9% 0.00 0.00 0.00 0.00

Total Emissions -0.2% 1.76 1.75 -3.5% 1.22 1.18 -0.00 -0.04

Table 320: Recalculation difference of Hg emissions [t] with respect to submission 2019.

1990 2017 Absolute Diff. Hg emissions [t] ∆% Subm.

2019 Subm. 2020

∆% Subm. 2019

Subm. 2020

1990 2017



0.0% 0.79 0.79 -0.6% 0.29 0.29 -0.00 -0.00

1.A.3 Transport 0.0% 0.00 0.00 0.2% 0.00 0.00 - 0.00

1.A.4 Other Sectors 0.0% 0.43 0.43 17.0% 0.15 0.18 0.00 0.03

1.A.5 Other = 0.00 0.00 0.0% 0.00 0.00 - 0.00

1.B Fugitive Emissions = NA NA NEW NA 0.00 NA 0.00


-7.5% 0.58 0.53 -12.0% 0.41 0.36 -0.04 -0.05

3 Agriculture = 0.00 0.00 = 0.00 0.00 - -

5 Waste = 0.05 0.05 0.1% 0.04 0.04 - 0.00

Total Emissions -1.9% 2.21 2.17 -2.1% 1.05 1.03 -0.04 -0.02

Table 321: Recalculation difference of Pb emissions [t] with respect to submission 2019.

1990 2017 Absolute Diff. Pb emissions [t] ∆% Subm.

2019 Subm. 2020

∆% Subm. 2019

Subm. 2020

1990 2017



0.0% 5.59 5.59 -5.7% 2.30 2.17 -0.00 -0.13

1.A.3 Transport 10.2% 162.93 179.54 38619.7% 0.01 4.62 16.61 4.60

1.A.4 Other Sectors -1.8% 7.52 7.38 18.6% 1.90 2.25 -0.14 0.35

1.A.5 Other = 0.00 0.00 0.0% 0.00 0.00 - 0.00



= 37.41 37.41 = 9.07 9.07 - -

3 Agriculture -49.2% 0.01 0.00 -53.9% 0.01 0.00 -0.00 -0.00

5 Waste = 1.02 1.02 0.6% 0.00 0.00 - 0.00

Total Emissions 7.6% 215.93 232.41 31.1% 15.66 20.54 16.49 4.87



Table 322: Recalculation difference of PAH emissions [t] with respect to submission 2019.

1990 2017 Absolute Diff. PAH emissions [t] ∆% Subm.

2019 Subm. 2020

∆% Subm. 2019

Subm. 2020

1990 2017



0.0% 0.06 0.06 -2.7% 0.22 0.22 0.00 -0.01

1.A.3 Transport 1.7% 0.29 0.29 -2.3% 0.35 0.34 0.00 -0.01

1.A.4 Other Sectors -7.6% 12.39 11.45 -5.6% 6.91 6.52 -0.94 -0.39

1.A.5 Other 0.0% 0.00 0.00 0.1% 0.00 0.00 - 0.00



0.0% 7.14 7.14 0.1% 0.25 0.25 0.00 0.00

3 Agriculture -67.2% 0.25 0.08 -44.4% 0.08 0.04 -0.17 -0.03

5 Waste = 0.00 0.00 = 0.00 0.00 - -

Total Emissions -5.5% 20.13 19.03 -5.5% 7.83 7.39 -1.10 -0.43

Table 323: Recalculation difference of Dioxin/Furan (PCDD/F) emissions [g] with respect to submission 2019.

1990 2017 Absolute Diff. Dioxin/Furan emissions [g] ∆% Subm.

2019 Subm. 2020

∆% Subm. 2019

Subm. 2020

1990 2017



0.0% 1.68 1.68 -4.9% 3.94 3.75 0.00 -0.19

1.A.3 Transport 8.6% 3.83 4.16 -4.9% 1.65 1.57 0.33 -0.08

1.A.4 Other Sectors 4.1% 42.13 43.87 -13.8% 24.18 20.84 1.73 -3.34

1.A.5 Other 0.0% 0.00 0.00 -1.2% 0.00 0.00 - -0.00



0.0% 42.85 42.85 0.0% 6.78 6.78 0.00 0.00

3 Agriculture = 0.18 0.18 = 0.06 0.06 - -

5 Waste = 20.29 20.29 1.7% 2.74 2.78 - 0.05

Total Emissions 1.7% 123.10 125.17 -8.7% 40.73 37.18 2.07 -3.54

Table 324: Recalculation difference of HCB emissions [kg] with respect to submission 2019.

1990 2017 Absolute Diff. HCB emissions [kg] ∆% Subm.

2019 Subm. 2020

∆% Subm. 2019

Subm. 2020

1990 2017



0.0% 0.29 0.29 -4.2% 0.64 0.61 0.00 -0.03

1.A.3 Transport 8.6% 0.77 0.83 -4.9% 0.33 0.31 0.07 -0.02

1.A.4 Other Sectors -1.7% 54.40 53.49 -7.9% 32.60 30.03 -0.91 -2.57

1.A.5 Other 0.0% 0.00 0.00 -1.2% 0.00 0.00 - -0.00



= 20.07 20.07 = 6.07 6.07 - -

3 Agriculture 27489.4% 0.04 10.15 15441.6% 0.01 1.81 10.12 1.79

5 Waste = 0.39 0.39 = 0.06 0.06 - -

Total Emissions 12.2% 76.23 85.50 -2.0% 40.21 39.40 9.27 -0.81



Table 325: Recalculation difference of TSP emissions [kt] with respect to submission 2019.

1990 2017 Absolute Diff.

TSP emissions [kt] ∆% Subm. 2019

Subm. 2020

∆% Subm. 2019

Subm. 2020

1990 2017



-3.7% 2.46 2.37 -22.6% 1.43 1.11 -0.09 -0.32

1.A.3 Transport 5.2% 8.69 9.15 1.8% 6.73 6.85 0.45 0.12

1.A.4 Other Sectors 1.7% 14.90 15.16 -3.2% 9.04 8.75 0.26 -0.29

1.A.5 Other = 0.02 0.02 = 0.02 0.02 - -

1.B Fugitive Emissions = 0.85 0.85 0.7% 0.43 0.44 - 0.00


0.1% 19.29 19.31 0.2% 15.94 15.96 0.02 0.03

3 Agriculture -0.9% 4.99 4.95 -0.2% 4.56 4.55 -0.04 -0.01

5 Waste = 0.35 0.35 0.3% 0.73 0.73 - 0.00

Total Emissions 1.2% 52.59 53.21 -1.0% 40.10 39.69 0.62 -0.41

Table 326: Recalculation difference of PM10 emissions [kt] with respect to submission 2019.


PM10 emissions [kt] ∆% Subm. 2019

Subm. 2020

∆% Subm. 2019

Subm. 2020

1990 2017



-3.7% 2.27 2.18 -22.3% 1.30 1.01 -0.08 -0.29

1.A.3 Transport 6.9% 6.93 7.41 4.2% 4.39 4.58 0.48 0.19

1.A.4 Other Sectors 2.2% 13.91 14.21 -3.7% 8.52 8.20 0.30 -0.32

1.A.5 Other = 0.02 0.02 = 0.02 0.02 - -



0.2% 11.15 11.16 0.4% 7.99 8.02 0.02 0.03

3 Agriculture -1.0% 4.28 4.24 -0.6% 3.93 3.90 -0.04 -0.02

5 Waste = 0.28 0.28 0.7% 0.47 0.48 - 0.00

Total Emissions 1.7% 40.21 40.90 -1.3% 27.94 27.58 0.69 -0.36

Table 327: Recalculation difference of PM2.5 emissions [kt] with respect to submission 2019.


PM2.5 emissions [kt] ∆% Subm. 2019

Subm. 2020

∆% Subm. 2019

Subm. 2020

1990 2017



-3.5% 1.97 1.90 -21.8% 1.11 0.87 -0.07 -0.24

1.A.3 Transport 8.2% 5.98 6.48 8.1% 2.98 3.22 0.49 0.24

1.A.4 Other Sectors 3.0% 13.02 13.41 -4.4% 8.13 7.77 0.39 -0.36

1.A.5 Other = 0.02 0.02 = 0.02 0.02 - -



0.4% 3.81 3.82 1.8% 1.75 1.78 0.02 0.03

3 Agriculture -11.2% 0.41 0.36 -10.9% 0.31 0.28 -0.05 -0.03

5 Waste = 0.23 0.23 1.3% 0.31 0.32 - 0.00

Total Emissions 3.0% 26.37 27.17 -2.0% 15.61 15.30 0.80 -0.31



7.4 Planned improvements, including in response to the review process, and planned improvements to the inventory

Improvements made in response to the review process

Improvements made in response to the issues raised in the last CLRTAP stage 3 review pro-cess (UNITED NATIONS 2017) are summarized in Table 320. The improvements made in re-sponse to the review process under the NEC Directive 2019 are indicated in Table 321.

Planned improvements

Planned improvements on sectoral level are presented in the respective sectoral Chapters 3–6.

Goals

The overall goal is to produce emission inventories which are fully consistent with the 2014 CLRTAP Reporting Guidelines and the EMEP/EEA Air Pollutant Emission Inventory Guidebook. An improvement programme has been established to help meet this goal.

Linkages

The improvement programme is driven by the results of the various review processes, as e.g. the internal Austrian review, review under the European Union Monitoring Mechanism, under the UNFCCC and/or under the Kyoto Protocol, under the UNECE/LRTAP Convention and under Directive (EU) 2016/2284 on the reduction of national emissions of certain atmospheric pollu-tants. Improvement is triggered by the improvement programme that plans improvements sector by sector and also identifies actions outside the Umweltbundesamt.

The improvement programme is supported by the QA/QC programme based on the internation-al standard EN ISO/IEC 17020:2012.

Updating

The improvement programme is updated every year after each review.

Responsibilities

The Umweltbundesamt is responsible for the management of the improvement programme.



Table 328: Improvements made in response to the latest CLRTAP Stage 3 Review in 2017.

Finding CLRTAP Review 2017 Reference Improvement made Chapter

General (cross-cutting)

KCA: For the upcoming years Austria will focus mostly on improving the uncertainty analysis on the whole. The next step would be the implementation of approach 2 of the KCA. The ERT welcomes these plans and encourages Austria to include approach 2 for the KCA in its future submissions.

Para 12, 27

Austria considers implementing approach 2 of the KCA as well as improving the uncertainties for future submissions.

-

QAQC: Austria has elaborated and implemented a quality assurance/quality control (QA/QC) plan in accordance with the EMEP/CORINAIR Guidebook (Inventory Management Chapter). This includes general QC procedures (tier 1) as well as source category-specific procedures (tier 2) for categories and for those individual categories in which significant methodological revisions and/or data revisions have occurred. The ERT encourages Austria to keep expanding the QA/QC activities in future submissions.

Para 23 Austria considers keeping expanding its QA/QC activities for future submissions.

-

Transparency: The ERT encourages Austria to continue improving the transparency of the IIR by providing more details on methodologies and tier level implementations for each of the sector presented in the IIR.

Para 27 Please refer to the sectoral chapters.

-

Energy (stationary)

Transparency: The ERT encourages Austria to include the answers that were provided to questions raised by the ERT during the 2017 review week in future submissions (see sub-sector specific recommendations).

Para 30 Please refer to category specific paragraphs below.

-

Consistency: The time series are in general consistent for the energy sector. Austria has justified most of the identified outliers but the ERT encourages Austria to include explanations for all large fluctuations highlighted during the stage 2 review in the IIR report.

Para 32 Please refer to category specific paragraphs below.

-

1.A.1.a Public electricity and heat production – NOx, SOx and TSP: The ERT notes that large point source emission measurements are the basis for the reported emissions. During the review Austria provided the share of emissions measured for the year 2000 and the year 2015 as well as an explanation for the decreasing trend of this share throughout the time series. The ERT encourages Austria to include similar information in the IIR in order to increase transparency.

Para 39 Information about the share of reported emissions and calculated emissions has been included in the relevant chapter of category 1.A.1.a.

Chapter 3.1.3.1

1.A.1.a Public electricity and heat production – NMVOC and NH3: The ERT notes that emission factors for NMVOC and NH3 for combustion installations > 50 MWth aren’t presented in the IIR. During the review Austria provided these emission factors by fuel type for the year 2015. The ERT encourages Austria to include similar information in the IIR in order to increase transparency.

Para 40 NMVOC and NH3 emission factor information has been included in relevant chapter of category 1.A.1.a.

Chapter 3.1.3.1




1.A.1.a Public electricity and heat production – NOx: The ERT tried to recalculate emissions by using activity data and emission factors from table 65 in the IIR but the calculated emissions weren’t consistent with the NFR data. Austria answered that the NOx emission factor of heavy fuel oil was misleading in the table. The ERT encourages Austria to correct the table accordingly.

Para 41 Emission factors have been updated in table 65.

Chapter 3.1.3.1

1.A.1, 1.A.2, 1.A.3.e.i, 1.A.4 Stationary Combustion –SOx: The ERT noted that according to the IIR, the emissions of SOx are not applicable (“NA”) for the combustion of natural gas and biogas while the EMEP/EEA GB 2016 suggests emission factors for SOx for natural gas. In that case the biogas contains sulphur. For example, biogas has an SOx emission factor of 19,2–25 g/GJ in the Danish IIR and an SOx emission factor of 10 g/GJ in the Finnish IIR. No emission factor could be a result of a total desulphurization, which is not common in Europe. If there are H2S emission limit values for biogas, an emission factor could also be deduced to estimate the SOx emissions. The ERT recommends that Austria investigates and estimates SOx emissions from biogas combustion and estimates SOx emissions from natural gas combustion.

Para 42 SO2 emissions from natural gas combustion have been estimated.

NFR tables, Chapters 3.1.3, 3.1.4, 3.1.5, 3.1.6

1.A.2.g – SO2: The ERT tried to recalculate emissions by using activity data and emission factors from table 101 in the IIR but the calculated emissions weren’t consistent with the NFR data. Austria answered that the SO2 emission factor of industrial waste had been revised from 130 g/GJ to 11g/GJ because the fuel, which was reported in the energy statistics, was mainly used in pulp and paper and wood manufacturing industries and the ”waste” was more equal to solid biomass. Therefore the emission factor for fuel wood had been selected. Austria will update the table 101 accordingly for the next submission.

Para 43 Emission factors have been updated accordingly.

Chapter 3.1.4.8

1.A.5.a Other stationary – All pollutants: In source category 1.A.5.a all emissions are flagged as “NO”. However in the IIR (p. 141), Austria had written that the emissions from military facilities were included in 1.A.4.a. Austria answered it was a mistake and will change the notation key to “IE” for the next submission.

Para 44 The notation keys were changed in the NFR tables since submission 2018.

NFR tables

1.A.4.b.i Residential – NMVOC: The ERT notes an increase of the NMVOC emissions in the residential sector. Austria answered that the increase of NMVOCs was due to added emissions from char coal use which was estimated for the first time in the 2017 submission. The amount of char coal was 267 TJ in 2015 and an emission factor of 2000 g NMVOC/GJ had been selected. This led to additionally 0.5 kt of NMVOC in 2015. The ERT recommends that Austria explains this new source of NMVOC emissions in the IIR to increase transparency.

Para 45 Due to substantial changes in the emission model for residential fuel combustion (in submission 2018) the finding should be obsolete.

Chapter 3.1.6




Energy (mobile)

1.A.3.b.iv – PM2.5: For category 1.A.3.b.iv, PM2.5 emissions are indicated as “IE” and the ERT asked where these emissions are included. The Party answered that PM2.5 emissions from mopeds and motorcycles should be reported as “NE” and not as “IE” as there are no CS measurements for PM2.5 exhaust emissions of 2-wheelers in Austria and the Guidebook suggests no calculation method for estimating those emissions according to Tier 3 (EMEP/EEA Update Dec. 2016 p.57). Austria will consider implementing the suggested Tier 2 default PM2.5 emission factors for mopeds and motorcycles in the emission model NEMO for the next submission. Although the contribution of this source is under the 2% threshold compared to national total, it is recommended that the Party calculates and reports these emissions in the next submission.

Para 57 The suggested Tier 2 (EMEP/EEA 2016) default PM2.5 EFs for mopeds and motorcycles have been implemented in the emission model NEMO since submission 2018.

Chapter 3.2.6

1.A.3.b.vi, 1.A.3.b.vii – PMs, HMs: Emissions from category 1.A.3.b.vi are reported as “NA” and the ERT asked the Party to explain the reason. The ERT also noted that "PM emissions from tyre and brake wear are included in road abrasion"; nevertheless, the ERT wants to encourage Austria to provide separate estimates for both sub-categories in future submissions. In any case, the notation key “IE” should be used instead of “NA”, since the emissions from 1.A.3.b.vi are included in 1.A.3.b.vii. Austria answered that emissions from 1.A.3.b.vi tyre and break wear are definitely included in 1.A.3.b.vii automobile road abrasion. Hence, the notation key indeed should be “IE” instead of “NA”. The Party will discuss if the emissions model NEMO can provide PM2.5 non-exhaust emissions for tyre/break wear and road abrasion separately. The ERT welcomes this plan.

Para 58 The separate reporting of PM2.5 non-exhaust emissions from tyre/break wear and road abrasion has been implemented in the emission model NEMO since submission 2018.

NFR tables, Chapter 3.2.6

1.A.3.b.vi, 1.A.3.b.vii – PMs, HMs: Following up on a relevant question from previous Stage 3 review report (2010, Transport, Category issue 5), the ERT wants to encourage Austria to provide estimates for “Additional HMs” for the categories 1.A.3.b.vi, 1.A.3.b.vii, although these are not mandatory to report.

Para 59 Austria has included this issue in it’s sectoral improvement plan, but considers this as “not of high priority” due to the non-mandatory reporting obligation

-




1.A.4.a.ii – All pollutants: Following up on a relevant question from previous Stage 3 review report (2010, Transport, Category issue 6), the ERT wants to encourage Austria again to provide separate emission estimates for categories 1.A.4.aii, 1.A.4.bii (commercial/institutional: mobile, and residential: household and gardening (mobile), respectively). Currently, the emissions from 1A4aii are included in 1.A.4.bii. Austria clarifies this in the IIR and mentions that a new study on fuel consumption and pollutant emissions of NRMM is considered for future submissions. Then, input data for the off-road sector will be updated and recalculated with the model GEORG. The ERT welcomes this plan.

Page 16 Emissions from 1.A.4.bii. Residential: household and gardening (mobile) are reported separately. Currently there is neither a statistical basis nor any new study on NRMM which would enable Austria to report emissions from 1.A.4.aii. Commercial/institutional separately. So, commercial/ institutional NRMM are included in 1.A.2.g.7 Industry and 1.A.4.c.2 Agriculture and Forestry. This information and the cross-reference are included since IIR 2018.

Chapter 3.2.7.4

Fugitive Emissions

1.B.1.b – All pollutants: In source category 1.B.1.b all emissions are flagged as “NO”. Austria explained that all emissions from the solid fuels transformation were reported under category 1.A.2.a. The ERT recommends that Austria changes the notation keys from “NO” to “IE” or “NA” and explains the allocation of the emissions in the IIR.

Para 46 Notation keys in category 1.B.1.b were corrected for all pollutants; an explanation for the allocation of the emissions is given. This recommendation has been implemented in submission 2018.

NFR tables; Chapter 3.3.1

1.B.2.a and 1.B.2.b – NMVOC: During the review the ERT tried to recalculate emissions by using activity data and emission factors from tables 172 and 173 in the IIR but the calculated emissions weren’t consistent with the NFR data. Austria answered during the review that these tables were misleading. The ERT encourages Austria to correct these tables in order to be consistent.

Para 47 Tables 172 and 173 of the IIR 2017 (Table 214 and Table 215) in the current IIR) were corrected and completed to ensure consistency with the NFR tables.

Chapters

3.3.3

3.3.4

1.B.2.a.iv – All pollutants: In source category 1.B.2.a.iv all emissions are flagged as “NA” (except NMVOC). The ERT recommends that Austria changes the notation keys from “NA” to “IE” and explains the allocation of the emissions in the IIR.

Para 48 Notation keys in category 1.B.2.a.iv were corrected for all pollutants, an explanation for the allocation of the emissions is given. This recommendation has been implemented in submission 2018.

NFR tables, Chapter

3.3.1

Industrial Processes and Other Product Use

Comparability: Methods for many sectors are country-specific and in some cases the emission factors used are not expressed in a way which is compatible with the factors provided in the Guidebook. As a result, it is difficult to compare the country-specific methods with those recommended in the Guidebook and to identify if these country-specific methods result in estimates that are significantly higher or lower than would be obtained using Guidebook methods. The ERT therefore recommends that the Party provides additional information that will aid comparisons with the Guidebook – for example by providing country-specific factors expressed on the same basis as those in the Guidebook wherever possible.

Para 64 Austria plans to include information on the comparison of the applied country-specific EF with the GB factors for next submission.

-




Accuracy: The Party includes an assessment of uncertainty in the IIR for individual NFR categories and pollutants within the industrial processes sector. This indicates that the uncertainty ranges from 20% to 200%, although it is not clear to what extent these assessed uncertainties are then used to prioritize improvements. For example, the estimates for PM2.5 from 2.A.1, 2.A.2 and 2.A.5 are all reported to have the highest uncertainty but there is no discussion of whether improvements are feasible or planned. The ERT therefore encourages the Party to provide more contexts for the improvement options: where emission estimates are most uncertain, what options exist to improve them, and what country-specific barriers are there to collecting better data.

Para 65 In submission 2018 uncertainties have been improved as national plant-specific data (NMVOC for 2.B.10) has been included in the inventory.

Chapter 4.1.4

2.A.1, 2.A.2: The ERT asked for clarification on the reporting of emissions from cement and lime kilns, since the approach to reporting does not seem to be consistent across all member states. The Party confirmed that pollutants other than particulate matter are reported in 1.A.2.f, while for particulate matter, emissions are reported in 2.A.1 & 2.A.2. This is consistent with the Guidebook, but the Party agreed that, for 2.A.1, changing the notation key for pollutants other than particulate matter from the current “NA” to “IE” would improve transparency. The Party indicated that this would be done in the next submission. The ERT noted that the implied emission factors for particulate matter from 2.A.1 are significantly lower than the 2016 Guidebook factors for uncontrolled processes: the Party stated that abatement technologies are commonly used at Austrian cement works.

Para 69 Austria clarified its reporting and revised its notation keys (since submission 2018).


2.A.5.a: The ERT notes that country-specific methods are used for this sector. The emission factors are specific to particular minerals, whereas those in the Guidebook are generic for all minerals, but many of the Austrian factors are higher than the generic Guidebook factor, so that the Austrian approach does yield higher estimates. The Party commented, however, that the country-specific factors also cover 2.A.5.c, and so the ERT concludes that it is plausible for Austrian factors to be higher than the generic Guidebook factor. The ERT encourages Austria to include information on the comparison of EFs in the sectoral QA/QC section of the IIR.

Para 70 Austria plans to include information on the comparison of the applied country-specific EF with the GB factors for next submission. The notation key of source category 2.A.5.c was changed to IE (since submission 2018).

NFR tables; Chapter

4.2.1




2.A.5.b: The ERT notes that country-specific methods are used and that PM2.5 emissions for 2.A.5 are subject to an uncertainty of 200%. A single emission factor is taken for all construction activity which is comparable to the Guidebook factor for the construction of houses (the lowest of the four factors in the GB, with significantly higher emission factors for apartments, non-residential construction and road construction). The Guidebook factors can be modified in order to account for local conditions (abatement, soil moisture etc.). The Austrian method does distinguish between building construction and road construction. The ERT recommends that: a) Austria should calculate emissions of PM2.5 using the Guidebook approach in order to determine how those estimates compare with the country-specific method, and b) if the two methods give significantly different results, either provide an appropriate level of justification for continuing to use the country-specific method given the uncertainty of that method, or use the Guidebook method instead.

Para 71 Austria plans to include information on the comparison of the applied country-specific EF with the GB factors for next submission.This improvement is planned for the next submission. Currently, data on different types of buildings are not being fully investigated.

Chapter4.2.2

2.B.10: In response to a review question, the Party confirmed that the Austrian inventory does include emission estimates for 2.B.10.b but that these are reported in 2.B.10.a. The Party agreed that the notation key “IE” would be used in future submissions.

Para 72 Austria revised the notation keys as indicated during the review (since submission 2018).


2.C.1 Iron & Steel: The ERT noted that some factors for this sector are referenced to earlier versions of the Guidebook. The Party responded that the factors actually corresponded to the values given in the 2016 Guidebook and that they would update the reference in future.

Para 73 This information is included in the IIR (since submission 2018).

Chapter

4.4.1

2.C.3 Secondary aluminium: The ERT noted that the Party reports lead emissions for this category but not particulate matter. Aluminium production data are confidential but lead emissions from the sector were 0.3% of national totals in 2005 and 0.2% of national totals in 2015. So, the ERT believes that emissions of particulate matter are likely to be of similar significance, but it is unlikely to exceed the threshold of significance. The ERT recommends including emission estimates for TSP, PM10 and PM2.5 in the next submission.

Para 74 The calculations have been improved according to the 2016 GB and particulate matter emissions are included since submission 2018.

NFR tables, Chapter

4.4.2

2.C.5 Secondary lead: The ERT noted that the Party reports lead emissions for this category but not particulate matter. Lead production is given as 24 kt in both 2005 and 2015, so applying the 2016 Guidebook Tier 1 factor for PM2.5 would yield an emission estimate of 0.06 tonnes for both years, which is well below the 2% threshold of significance. The ERT recommends including emission estimates for TSP, PM10 and PM2.5 in the next submission.

Para 75 The calculations have been improved according to the 2016 GB and particulate matter emissions are included since submission 2018.

NFR tables, Chapter

4.4.2




2.C.7.c Other metal production: In response to a review question, the Party stated that emissions of metals from this sector are reported in 1.A.2.b.

Para 76 In submission 2018, the calculations have been improved according to the 2016 GB and particular matter emissions are now included. Emissions from Copper production have been reallocated from 1.A.4. to 2.C.7.c.

NFR tables

Product Use

Comparability: Methods for the solvents sector are mostly country-specific and it is not possible to compare the country-specific methods with those recommended in the Guidebook and to identify if these country-specific methods result in estimates that are significantly higher or lower than would be obtained using Guidebook methods. However, the Party estimates the uncertainty in NMVOC emissions from 2.D as 20% so among the lowest for NFR 2. The Party has given a detailed description of the method used to estimate NMVOC emissions for 2.D.3 so the ERT is satisfied that the country-specific method is able to produce more accurate results than the default methods in the Guidebook. The ERT encourages the Party to provide additional information that will aid comparisons with the Guidebook – for example by generating per capita emission factors for 2.D.3.a from the Austrian estimates for this sector, which can then be compared with the Tier 1 emission factor in the Guidebook.

Para 81 As discussed in the respective chapter, the method for the calculation of solvent use has been revised in submission 2019. Updated uncertainties of NMVOC emissions are as well as information on per capita EFs per SNAP are included in the respective chapter.

Chapter

4.1.4

4.5.2

Accuracy: The Party includes an assessment of uncertainty in the IIR for individual NFR categories and pollutants within the solvents sector – these are relatively low compared with the uncertainties quoted for some categories within the industrial processes sector. ERT encourages the Party to provide information tangling the uncertainty assessment the IIR.

Para 82 As discussed in the respective chapter, the method for the calculation of solvent use has been revised in submission 2019. Updated uncertainties of NMVOC emissions are as well as information on per capita EFs per SNAP are included in the respective chapter.

Chapters

4.1.4 4.5.2

2.D.3 Solvent use: Table 199 in the IIR presents implied emission factors for NMVOC from solvent use sectors. These factors are expressed in terms of g/t solvent used and so should not exceed the value 1,000,000. Some of the implied factors are actually greater than this and the Party has explained that this is an error in the way in which the AD are calculated and that they are working on a solution to this problem. The ERT recommends that the Party provides corrected emission factors and/or activity data in future submissions.

Para 83 Information on activity data and IEFs as used in the currently improved solvents model has been included in the sectoral chapter.

Chapter

4.5.2




2.G Other product use: The Party confirmed that for use of tobacco, Austria only reports emissions of particulate matter. The 2016 Guidebook provides emission factors for many other pollutants including NOx, CO, NMVOC, NH3, metals and POPs. No activity data was available and so no technical correction could be made. The ERT recommends that emission estimates for all pollutants listed in the Guidebook are included in the next submission.

Para 84 Calculations using the EFs provided in the 2016 Guidebook have been included since submission 2018.

Chapter

4.5.4

Agriculture

Accuracy: The ERT encourages Austria to further extend the uncertainty analysis of the activity data by including other animal categories in the inventory, such as sheep, goats, laying hens and turkeys in order to further promote the reliability of the inventory data.

Para 95 Austria’s uncertainty analysis includes all livestock categories for which emissions were reported. Source category 3.B.4 Other Livestock comprises uncertainties for goats, poultry, horses and other animals.

Chapter 5.2.4

3.D.f Use of pesticides – HCB: The ERT notes that Austria does not estimate emissions of HCB from the use of pesticides (3.D.f) reporting as not occurring (“NO”). However, the ERT informed the Party that there has been a consumption of pesticides between 2011 and 2014 according to the Eurostat Agri-environmental indicator. Austria clarified that the EMEP/EEA GB 2016 provides default emission factors for 11 pesticides (Table 3-1). All of the listed pesticides are not occurring in Austria as they are forbidden compliant with the Stockholm Convention on Persistent Organic Pollutant and European legislation (POP Regulation (EG) Nr. 850/2004). However, Austria agrees that there is some pesticide consumption in the country. As for these types of pesticides no emission factors and methodologies are available in the Guidebook, Austria considers to use the notation key “NA” instead of “NO” in the next submission. The ERT encourages the Party to report emissions of HCB from relevant pesticides when reliable methodologies are available.

Para 89, 98, 99

From submission 2018 onwards Austria applies the notation key “NA” instead of “NO” for source category 3.D.f.

NFR tables

Waste

Accuracy and uncertainties: Austria describes QA/QC procedures and uncertainty analyses for waste sector in its IIR. The ERT encourages Austria to continue the development of an uncertainty analyses.

Para 105 An estimate of the uncertainty for emissions of the sector 5.D has been included since IIR 2018.

Chapter 6.2.4

Improvement: There are no improvements mentioned for the waste sector in Austria’s IIR. The ERT encourages Austria’s to plan improvements for waste sector regarding the transparency of the inventory.

Para 106 In 2018, it was planned to carry out a study on the amounts of landfill gas recovered. This information was included in the IIR 2018.

Chapter 6.2.6 (IIR 2018)




5.A Solid waste disposal on land: Descriptions of emission calculations and activity data estimations are comprehensive and transparent. Austria uses notation key “IE” (included elsewhere) for NOx and SOx emissions. The ERT assumed according to the previous Stage 3 review that these emissions are from landfill gas recovery. The ERT encourages Austria to provide an explanation about that in IIR.

Para 107 An explanation that NOx and SO2 emissions are covered in the energy sector, as the landfill gas is used for energy recovery, has been added since submission 2018.

Chapter 6.2.1

5.B Biological treatment of waste: Austria reports emissions in 5.B.1 biological treatment of waste – composting. The calculations are described in good quality and in detail. For the sub-sector 5.B.2 anaerobic digestion at biogas facilities Austria reports the notation key “NA” (not applicable). The ERT encourages the Party to provide an explanation in IIR tangling the use of notation key.

Para 108 In submission 2019 Austria included NH3 emissions from biogas facilities, which were calculated under NFR sector Agriculture, but reported in sector Waste. Methodological descriptions have been added in the relevant chapter.

Chapters 6.4.1. 5.3.4

5.C Incineration of waste: According to NFR tables Austria reports emissions in 3 sub-sectors industrial waste incineration, clinical waste incineration and cremation. For sewage sludge, municipal and industrial waste incineration activity data is only estimated for the years 1990–1991. For open burning of waste the notation key “NO” (not occurring) is used. The ERT encourages Austria provide a short description about the open burning of wastes in the IIR. Austria should clarify in its IIR if such activities also occur if forbidden.

Para 109 Due to national legislation any waste incineration/co-incineration needs an explicit permit. However, POP emissions from illegal waste co-incineration in the residential sector had been considered in emission measurements and emission factors used for calculation of emissions from 1.A.4.

Chapter 6.5.1

5.D Wastewater handling: Austria calculated emissions for the sub-sector 5.D.1 domestic wastewater handling. Calculations were provided for the first time. The ERT accepts Austria’s approach of activity data estimation and chosen EF. Regarding NH3 emissions from 5.D.1 the ERT encourages to add a description of latrine uses in Austria in the IIR of the next submission.

Para 110 A description of latrine uses in Austria is included since IIR 2018.

Chapter 6.6.2

5.E Other waste: Austria reports the notation key “NO” (not occurring) for 5.E. In EMEP/EEA Guidebook 2016 sludge spreading, car fires and building fires emissions calculations are described for this sub-sector. The ERT encourages investigating the possibility to obtain activity data for car and building fires. Default emission factors for calculations could be used. In most European countries fire and rescue services collect information about fires. In the EMEP/EEA Guidebook 2016 EFs regarding the number of fire accidents are provided.

Para 102, 111

Emissions for source category 5.E have been added based on national data on car and house fires and the emission factors from the EMEP/EEA guidebook since submission 2018.

Chapter 6.7



Table 329: Improvements made in response to the NEC Review in 2019.

Finding NEC Review 2019 Reference Improvement made Chapter

National Total

0A National Total – National Total for the Entire Territory - Based on Fuel Sold/Fuel Used, BaP, PAHs, 1990–2017: For National Total and the 4 PAH species and all years the TERT noted that Austria does not estimate emissions. To the question on the issue Austria responded that they will put this on the improvement list.

AT-0A-2019-0001

This improvement will be finished by the next submission.

Chapter 2.4.1.1

0B National Total for Compliance Assessment, NOx, NH3, 2010–2017: The TERT noted that there is a lack of clarity regarding the calculation of National Totals (rows 141 and 143). In response to the TERT’s request for clarification, the Member state responded: "Austria's “NATIONAL TOTAL FOR COMPLIANCE” (row 144) for the years 2010 to 2017 is based on 'fuel used'. For the years 1990-2009 the “NATIONAL TOTAL FOR COMPLIANCE” (row 144) is reported as ‘NR’ because there is no compliance for those years under the NEC-Directive. For Austria's comparison with the national emission ceilings from 2010 onwards (Austria’s Total for Compliance) both emissions from fuel export (sector Transport) and emissions from approved adjustments have to be subtracted from the National Total based on fuel sold. Austria calculated emission amounts as follows (e.g. for 2017 and NOx emissions): Sum of emissions from all categories excluding emissions from sector Transport 1A3 (rows 14 to 24 and 39 to 140; resulting in 70.48 kt NOx) plus emissions from sector Transport ‘Fuel used’ (row 152; 61.00 kt NOx) plus ‘Adjustments’ (row 143) -37.38 NOx = 94.10 kt NOx. For NH3 the same formula is applied. Pursuant to the provisions of the NEC Directive Austria adjusted annual national emission inventories only for those years where national emission reduction commitments would be exceeded without adjustment application."

AT-0B-2019-0001

The new ANNEX I tables in NFR-19 format contain formulae that make the calculation of the national compliance total transparent

NFR Tables

2.5

Energy (stationary)

1A1b Petroleum Refining, Cd, 2016, 2017: For category 1A1b Petroleum Refining for the pollutant Cd and years 2016 and 2017, the IEF ratios are outliers when compared to other Member States. The TERT notes that reported emissions are higher (>4 times higher) than when a reference value is calculated using Tier 1 EFs from the 2016 EMEP/EEA Guidebook. In response to a question raised during the review, Austria agreed that their national emission factors were much higher and thus Austria might be over-estimating this source. Austria stated that this issue will be investigated and revised in the next submission.

AT-1A1b-2019-0002

Cd emissions from 1A1b refineries have been re-estimated using a method developed by CONCAWE. This results in higher Cd emissions 1990 but lower Cd emissions 2017.

Chapter 3.1.3.2




1A3b Road Transport, SO2, NOX, NH3, NMVOC, PM2.5, 2000–2017: Austria has the option to use road transport emissions estimated by fuel used for compliance purposes. The TERT noted that there is a lack of transparency regarding whether only road transport or other transport and/or mobile machinery are estimated on a fuel used basis for compliance purposes. The TERT recognise that this is partly due to the format of the Annex I reporting template. In response to a question raised during the review, Austria explained that road transport by fuel used is used for compliance purposes, and all other sources are calculated on a fuel sold basis.

AT-1A3b-2019-0001

A clear explanation is now included.

Chapter 3.2.6

1A3bvi Road Transport: Automobile Tyre and Brake Wear, Pb, 1998–2017: For Pb emissions from 1A3bvi Road Transport: Automobile Tyre and Brake Wear the TERT noted that emissions are reported as 'NA' in the 2019 submission. However, default emission factors are provided in the 2016 EMEP/EEA Guidebook and therefore emission estimates should have been provided for completeness. In response to a question raised during the review, Austria agreed with the finding and provided revised estimates for 1990, 2005, 2016 and 2017 and stated that the emissions will be included in the next submission. The TERT agreed with the revised estimate provided by Austria.

AT-1A3bvi-2019-0001

The inclusion of Pb emissions from Tyre and Break wear lead to an increase in Pb emissions over the entire time series.

Chapter 3.2.6

1A3c Railways, NOX, NMVOC, SO2, NH3, PM2.5, 2004, 2005, 2010, 2011: For 1A3c Railways, all pollutants and years 2004–2005 and 2010–2011, the TERT noted that there are large changes in the activity data between 2004 - 2005 and 2010 - 2011 for this sector. This causes large changes in the pollutant emissions during these years. In response to a question raised during the review Austria agreed with the finding but stated that as this is not a key category, it was not of high priority to resolve the issue. The TERT noted that the issue is below the threshold of significance for a technical correction.

AT-1A3c-2019-0001

This item is included in the improvement plan and dicussed in the planned improvements.

Chapter

3.2.7.2

Energy (mobile)

1A3dii National Navigation (Shipping), NOX, 2008: For 1A3dii National Navigation, NOX, 2008, the TERT noted that significant recalculations had occurred between the 2018 and 2019 inventory submissions for this year, but that no reasons for the change were provided in the IIR. In response to a question raised during the review, Austria identified that the emission estimates were in fact incorrect for this year and that this would be corrected in future submissions. The TERT noted that the issue is below the threshold of significance for a technical correction and related to a non-mandatory year.

AT-1A3dii-2019-0002

The mistake is corrected. NFR Tables




Fugitive Emissions

1B2d Other Fugitive Emissions from Energy Production, Geothermal Energy Extraction, NH3, Hg, As, 1990–2017: For category 1B2d Other Fugitive Emissions from Energy Production, pollutants NH3, Hg and As for all years the TERT noted that the notation key 'NE' is used. In response to a question raised during the review, Austria explained that they are in contact with the Austrian Association of Gas and District Heating Supply Companies to clarify whether emissions from geothermal energy are occurring in Austria.

AT-1B2d-2019-0001

Recalculations of NH3- and Hg-emissions for the years 2005-2017 are due to the new estimation of fugitive emissions from energy production in geothermal energy (subcategory 1.B.2.d) and lead to an increase of 0.0005kt NH3 and 0.0001kt Hg in 2017

Chapter 3.3.5

Agricultural Soils

3Da2a Animal Manure Applied to Soils, NH3, 2000–2010: For 3Da2a Animal manure applied to soils and NH3 the TERT noted that there is a lack of transparency regarding recalculations. This does not relate to an over- or under-estimate of emissions.

AT-3Da2a-2019-0001

Improvements of the methodological description have been implemented in the IIR.

Chapter

5.5.3.1

3Df Use of Pesticides, HCB, 1990, 2005, 2016, 2017: For category 3Df Use of Pesticides, pollutant HCB for years 1990, 2005, 2015, 2016 and 2017 the TERT noted that Austria reports 'NA'. In response to a question raised during the review, Austria indicated that due to the fact that the latest update of the guidebook version was published in October 2018 this issue could not be considered in the current submission. However, Austria will include it in its improvement plan and explained that there is a need for further investigation on the use of the relevant pesticides and possible impurities or by-products in Austria.

AT-3Df-2019-0001

Emssions are estimated and the category is described in the IIR.

NFR Tables

Chapter

5.5.6

Waste

5C1bv Cremation, SO2, Cd, PCBs, BaP, 1990–2017: For 5C1bv Cremation the TERT noted that there may be an under-estimate of emissions because some pollutant emissions (SO2, Cd, PCBs, BaP that were reviewed this year and BbF, BkF, IndP that were not reviewed this year) are not estimated although EFs are proposed in the 2016 EMEP/EEA Guidebook. Anyway, Austria reports the sum of the 4 PAHs. In response to a question raised during the review Austria indicated that it will consider the updated methodology proposed in the 2016 EMEP/EEA Guidebook in its next submission. The TERT noted that the issue is below the threshold of significance for a technical correction.

AT-5C1bv-2019-0002

SO2, Cd, and PCB emissions from 5.C.1.b.v cremation have been estimated

NFR Tables

Chapter6.5

Austria’s Informative Inventory Report (IIR) 2020 – Projections


8 PROJECTIONS

As outlined in the ‘Guidelines for Reporting Emission Data under the Convention on Long-Range Transboundary Air Pollution’ (ECE/EB.AIR/125, Update on 13 March 2014) § 44 Parties to the Gothenburg Protocol within the scope of EMEP shall regularly update their projections and report every four years from 2015 onward their updated projections for the years 2020, 2025 and 2030 and, where available, also for 2040 and 2050. Parties to the Proto-cols are encouraged to regularly update their projections and report every four years from 2015.

§ 45 Projected emissions for substances listed in paragraph 7 (i.e. sulphur dioxide (SO2), nitro-gen oxides (NOx), ammonia (NH3), PM2.5 and non-methane volatile organic compounds (NMVOCs etc.) and, where appropriate black carbon should be reported using the template within Annex IV to these Guidelines. Parties should complete the tables at the requested level of aggregation. Where values for individual categories or aggregated NFR categories are not available, the no-tation keys defined in paragraph 12 to these Guidelines should be used.

§ 46 Quantitative information on parameters underlying emission projections should be reported using the templates set out in annex IV to these Guidelines. These parameters should be re-ported for the projection target year and the historic year chosen as the starting year for the pro-jections.

Austria’s latest emission projections for the scenario ‘with existing measures’ for the year 2020, 2025 and 2030 are published in the report ‘Austria’s National Air Emission Projections 2019 for 2020, 2025 and 2030’ (UMWELTBUNDESAMT 2019d). The report includes background information to enable a quantitative understanding of the key socioeconomic assumptions used in the prep-aration of the projections. It updates previous projections for air pollutants published in 2017 (UMWELTBUNDESAMT 2017b).

The following table shows Austria´s national total emissions and projections based on fuel sold as well as on fuel used. Emissions have to be reported based on fuel sold under the UNECE/ LRTAP Convention as well as under the NEC Directive 2016/2284/EU. With respect to compli-ance under the NEC Directive, Austria reports emissions and projections based on fuel used. When referring to emissions based on ‘fuel used’, ‘fuel exports in the vehicle tank’ are not con-sidered. The revised NEC Directive sets ceilings for five air pollutants: nitrogen oxides (NOx), sulphur dioxide (SO2), non-methane volatile organic compounds (NMVOC), ammonia (NH3) and particulate matter (PM2.5).

The scenario “with existing measures” results in significant emission reductions by 2030 for all pollutants except NH3. The most substantial reduction (about 64% for fuel sold and 55% for fuel used) from 2005 until 2030 is projected for NOx, provided that the latest and new emission standards for road vehicles meet their specifications.

Emission reductions for the other pollutants are in the range from 27% to 48%; NH3 emissions, however, are projected to increase by 14–15% (see Table 321).

Austria’s Informative Inventory Report (IIR) 2020 – Projections


Table 330: Austrian national total emissions in kt and trend in comparison with the base year 2005 in % based on (a) fuel sold and (b) fuel used.

Pollutant Emission inventory 2019 Emission scenario Type of scenario

[kt] 1990 2005 2010 2015 2020 2025 2030

NOx

219.33 237.87 183.14 144.71 126.62 99.29 84.49 fuel sold

0.0% -23.0% -39.2% -46.8% -58.3% -64.5%

204.33 178.66 152.51 131.48 116.74 93.31 80.21 fuel used

0.0% -14.6% -26.4% -34.7% -47.8% -55.1%

SO2

73.76 25.47 15.86 12.81 13.58 13.41 13.31 fuel sold

0.0% -38% -50% -47% -47% -48%

72.98 25.42 15.83 12.78 13.55 13.36 13.27 fuel used

0.0% -38% -50% -47% -47% -48%

NMVOC

324.40 156.10 137.17 120.19 120.37 116.00 111.85 fuel sold

0.0% -12% -23% -23% -26% -28%

322.24 152.16 135.55 119.30 119.57 115.27 111.16 fuel used

0.0% -11% -22% -21% -24% -27%

NH3

65.19 62.70 65.70 69.09 69.47 70.51 71.57 fuel sold

0.0% 5% 10% 11% 12% 14%

65.15 62.17 65.40 68.85 69.22 70.24 71.28 fuel used

0.0% 5% 11% 11% 13% 15%

PM2.5

26.37 22.21 19.19 15.61 14.94 13.42 12.16 fuel sold

0.0% -14% -30% -33% -40% -45%

25.87 20.62 18.49 15.38 14.79 13.33 12.09 fuel used

0.0% -10% -25% -28% -35% -41%

Austria’s Informative Inventory Report (IIR) 2020 – Reporting of gridded emissions and LPS


9 REPORTING OF GRIDDED EMISSIONS AND LPS

According to the UNECE Convention on Long-Range Transboundary Air Pollution as well as under the NEC Directive parties are obligated to report gridded emissions and large point sources (LPS). Being in line with the revised 2014 CLRTAP Reporting Guidelines (ECE/EB.AIR.125) both datasets shall be reported every four years from 2017 onwards for the year x-2.

In submission 2017 Austria reported data on gridded emissions based on fuel sold and on fuel used as well as LPS data for 2015. The data for previous years (1990, 1995, 2000, 2005 and 2010) was reported in submission 2012161.

This chapter includes descriptions on input data, methodology and results of the Austrian grid-ded emissions for 2015 as well as on large point sources (LPS) for 2015, officially submitted in 2017162.

Therefore, this chapter remains unchanged since IIR 2017.

9.1 Gridded Emissions

9.1.1 Background Information

At the 36th session of the EMEP Steering Body it was suggested to increase the spatial resolu-tion of the EMEP grid from 50 km x 50 km to 0.1° x 0.1° in order to improve quality of monitor-ing. So, in the revised 2014 CLRTAP Reporting Guidelines (ECE/EB.AIR.125) the new “EMEP grid” refers to a 0.1° × 0.1° latitude-longitude projection in the geographic coordinate World Ge-odetic System (WGS) latest revision, WGS 84. Therefore, the spatial allocation of the current Austrian Air Emission Inventory had to be adapted accordingly. There was a need to adjust the base data and the statistical background to latest databases and updated GIS data.

The mandatory reporting of gridded emissions includes the following 14 pollutants: SOx, NOx, NH3, NMVOC, CO, PM10, PM2.5, Pb, Cd, Hg, PCDD/F, PAHs, HCB and PCBs.

The applied method is based on (ORTHOFER et al. 2002 and ORTHOFER 2007) but had to be adapted accordingly due to the improved resolution. So the number of grid cells for Austria in-creased from about 60 (50 km x 50 km) to 1 144 (0.1° × 0.1°).

9.1.2 Emissions according to the GNFR-Code

In Table 322 the NFR sectors are listed which were used for reporting of gridded emission data based on the Austrian Air Emission Inventory. This is in line with the EMEP/EEA GB 2016 (EEA 2016).

161 http://www.ceip.at/ms/ceip_home1/ceip_home/status_reporting/2012_submissions/ 162 http://www.ceip.at/ms/ceip_home1/ceip_home/status_reporting/2017_submissions/





Table 331: GNFR categories and corresponding NFR categories.

GNFR ID GNFR Name NFR categories Note

A_PublicPower Public Power 1.A.1.a

B_Industry Industry 1.A.1.b, 1.A.1.c, 1.A.2.a, 1.A.2.b, 1.A.2.c, 1.A.2.d, 1.A.2.e, 1.A.2.f.i, 1.A.2.g.viii, 2.A., 2.B, 2.C, 2.D.3.b, 2.D.3.c, 2.H, 2.I, 2.J, 2.K, 2.L

C_OtherStationary Comb

Other stationary combustion

1.A.4.a.i, 1.A.4.b.i, 1.A.4.c.i, 1.A.5.a

D_Fugitive Fugitive Emissions 1.B.1, 1.B.2

E_Solvents Solvents 2.D.3.a, 2.D.3.d, 2.D.3.e, 2.D.3.f, 2.D.3.g, 2.D.3.h, 2.D.3.i, 2.G

F_RoadTransport Road Transport 1.A.3.b

G_Shipping Shipping 1.A.3.d.i(ii), 1.A.3.d.ii

H_Aviation Aviation 1.A.3.a.i(i), 1.A.3.a.ii(i)

I_Offroad Offroad 1.A.2.f.ii, 1.A.2.g.vii, 1.A.3.c, 1.A.3.e.i, 1.A.3.e.ii, 1.A.4.a.ii, 1.A.4.b.ii, 1.A.4.c.ii, 1.A.4.c.iii, 1.A.5.b

J_Waste Waste 5

K_AgriLivestock Agriculture – Livestock 3.B

L_AgriOther Agriculture – Other 3.D, 3.F, 3.I

M_Other Other emission sources - Not occurring

9.1.3 Allocation of emissions

The following chapter describes the GIS based method and the proxy data, which was used for the allocation of national emissions to the EMEP Grid. The same method was applied for data based on fuel sold and fuel used. The data was intersected with the EMEP Grid and weighted within ArcGIS 10.4. In a second step the emissions were distributed via database calculations.

Austria is located in central Europe and has a heterogeneous topography. The main part is in-fluenced by alpine climate with more balanced temperatures and precipitation, whereas the eastern part of the country is characterized by continental climate. So it was considered neces-sary to take into account the regional heterogeneity in case of source categories with a broad spatial distribution.

9.1.3.1 Applied data sources for gridded emission

Information about the main proxy data is listed in Table 323 and is also described in more detail below. These data are the basis for the disaggregation of the national emissions, which was carried out on NFR level. In a final step the results were aggregated to the GNFR sectors as it is required in the CLRTAP reporting template for the gridded emissions (Annex V).

It was not possible to create a fully homogenous set of proxy data that always refers to the year 2015, due to lack of data availability. The data sources cover a time frame from 2011 to 2016, e.g. economic activities on municipal level, where the latest data set is from 2011. This infor-mation is also included in Table 323.



Table 332: Overview of proxy data.

Data set Data description Data source Year Resolution/data specification

Topographic map Administrative units, territorial boarders according to the needed database

Federal Office for Metrology and Surveying (BEV)163

2011–2016 Cadaster

River network Danube, Shipping area BMLFUW164 2015 Vector data

Employees in the manufacturing industries sector

Economic activities on municipal level (NACE classification), register census 2011

Statistik Austria165 2011 Municipal level; cadaster

Population Population per municipality Statistik Austria 2015 Municipal level

Permanent settlement area

Statistical processed data according to Corine Landcover

Statistik Austria 2013 25 m raster

Corine Land cover 2012

Raster data on land cover Environment Agency Austria166

2012 25 x 25 m raster

Commuters Amount of commuters leaving place of residence

Statistik Austria 2014 Municipal level

Road and railway network

Vector data for classified road and railway network

Graph Integration Platform (GIP) Austria167

2016 Vector data

Traffic census points

Geo-referenced information on traffic census on motorways

ASFINAG168 2015 Points, coordinates

Register of buildings and dwellings

Geo-referenced information on dwellings and buildings

Statistik Austria 2016 Address data

Rural- urban typology

Statistical processed data Statistik Austria 2015 Municipal level

Animal livestock numbers

INVEKOS data base Agrarmarkt Austria (AMA)169

2012 1 km raster

Large Point Sources (LPS)

Geo-referenced information on power plants, large industrial plants

Official data sub-missions 2017 under Regulation (EC) No 166/2006 and Directive 2010/75/EU

2015 Address data

Waste treatment Geo-referenced information on large point plants in the waste sector (LPS); correlation with population numbers

Official data submissions 2017 under Regulation (EC) No 166/2006 and Directive 2010/75/EU, Statistik Austria

2015 Municipal level

163 http://inspire.ec.europa.eu/LMOS/federal-office-metrology-and-surveying-bev 164 https://www.bmlfuw.gv.at/ 165 https://www.statistik.at/web_de/statistiken/index.html 166 http://www.eea.europa.eu/data-and-maps/data/external/corine-land-cover-2012 167 http://www.gip.gv.at/ 168 http://www.asfinag.at/home-en 169 https://www.ama.at/Intro

http://inspire.ec.europa.eu/LMOS/federal-office-metrology-and-surveying-bev

https://www.bmlfuw.gv.at/

https://www.statistik.at/web_de/statistiken/index.html

http://www.eea.europa.eu/data-and-maps/data/external/corine-land-cover-2012

http://www.gip.gv.at/

http://www.asfinag.at/home-en

https://www.ama.at/Intro



Economic activities

There is a strong correlation between the NACE classification (ÖNACE 2008 classification) and the NFR sectors of manufacturing industries. The amount of employees in the different NACE sectors within the manufacturing industry sector at the municipal level was taken as basis to generate the proxy for the respective NFR sectors. These proxies were finally combined to the aggregated GNFR sector B_Industry.

Population and permanent settlement data

Data from population for 2015 is available from national official statistics at municipal level.

The permanent settlement area combines Corine Landcover data and economic statistics and is a data set compiled by Statistik Austria. The latest one is available for 2013 and in a resolution of 25 m.

As described before, the topographical heterogeneity within Austria had to be considered. So, the population data on municipal level and the permanent settlement area was combined for sectors and categories with a wide spatial distribution spectrum. As an example for this ap-proach the NFR sector Solvent Use can be mentioned.

Land use statistics

Land use statistics were taken from the Corine Land cover statistics as basis for soil related emissions which are included in GNFR sector L_AgriOther. The Corine Land cover also pro-vides the base for calculations of the permanent settlement areas, which was described above.

Traffic network and traffic census data

The river network as well as the road network builds the line based emission data. These vector data is intersected with the EMEP Grid. All shipping emissions are allocated to the Danube River.

The traffic network is taken from a national harmonized street and railway dataset. The prepara-tion of these proxies required a few steps. First the traffic network was divided in motorways, streets in built-up areas and rural traffic net. In a second step the different street levels were weighted in three different ways. The motorways were combined with traffic census data from measuring points. The main routes with intense traffic were weighted with a higher level than less frequented sections. The built-up areas were weighted with commuters in a working dis-tance of 1–4 km and local stationary inhabitants. For rural traffic commuters within a distance between 5 and 50 km the street segments were taken for assessment. It was assumed that the-se commuters leave their place of residence and travel all days. These weighted databases were finally combined with the national CLRTAP emission data according to the NFR subsec-tors. In a last step the NFR sectors were aggregated to the respective GNFR sectors. These calculations were done for all pollutants separately.

Register of buildings and dwellings

Geo-referenced information on dwellings and buildings (e.g. heating systems, age of buildings etc.) are the proxy data for emissions from stationary fuel combustion in buildings and in agricul-ture, forestry, fishing and fishing industries (NFR categories 1.A.4.b.i and 1.A.4.c.i). Due to the information in the register of buildings and dwellings an index was created to distribute the emissions of the Austrian Air Emission Inventory on federal level (BLI) combined with the usage of heating systems and type of buildings. These indices distinguish between all pollutants.



Rural- urban typology

Rural- urban typology is a statistical data base which defines the main regional centres and the urban areas trough population density, infrastructures, commuter traffic and reachability. This proxy was taken to calculate the transport emissions from GNFR sector I_Offroad.

Animal livestock numbers

For the GNFR sector K_AgriLivestock the animal livestock numbers taken from the INVEKOS data base, available as 1 km raster, were used as proxy. The respective animal categories are consistent with those included in the Austrian Air Emission Inventory on NFR level. Another ap-proach could have been the amount of employees within the farming business. However, the animal livestock numbers represent the reported emissions of manure management better than the employees as they are not relevant for emissions. So, the usage of livestock data is fully in line with the calculation of agricultural emissions from NFR sector Manure Management.

Large Point Sources

The large point emission sources were directly allocated to their grid cells considering two clas-ses of emission levels (emission high above and below 100 m). LPS data for 2015 are reported by Austrian plants according to Directive 2010/75/EU on industrial emissions (integrated pollu-tion prevention and control) (Large Combustion Plants – LCP) as well as under Regulation (EC) No 166/2006 on the establishment of a European Pollutant Release and Transfer Register. The required information on emission values, coordinates, stack heights etc. was matched for each relevant NFR sector and aggregated to the respective GNFR sectors to be in line with the CLRTAP reporting obligation (see reporting template Annex VI). For further information please refer to Chapter 9.2.

Waste treatment

Two different data bases have been taken as proxy for GNFR sector J_Waste. On the one hand the respective large point sources with activities in the waste sector have been used as proxy data for waste treatment. On the other hand the population in permanent settlement areas was applied for disaggregating the emissions from waste.

9.1.3.2 Austria’s allocation of emissions for the EMEP Grid

Method of allocation

Emissions from point sources were directly allocated to the coordinates of the individual emit-ters. Line based emissions and emissions from area sources were disaggregated from the na-tional total emissions to the described proxy data (see Table 323). In some cases, the set of proxy data could be used as one pure proxy. However, in several cases (e.g. traffic network) a combination and weighted proxy, respectively, was necessary.



Figure 51: EMEP Grid Austria – example for allocation of the motorway network and waterways (Danube).

A short and simple example of the allocation of the motorway network and waterways (Danube) is illustrated in Figure 51 to point out the method. The length of the segments within the grid cell is multiplied with the national emission divided by the total emissions.

9.1.4 Results of gridded data

In this chapter the EMEP grid results for the main pollutants NOx, SO2, NMVOC and NH3 as well as for PM2.5 based on fuel sold are presented. In the case of NOx there is a significant difference between results for fuel sold and fuel used, therefore maps have been generated for both.

Emissions of grid cells exceeding the national border have been adjusted proportionally. This methodology is only applied for the purpose of illustrating the results in the following maps.



9.1.4.1 Spatial distribution of NOx emissions in 2015

Figure 52: Spatial distribution of Austria´s NOx emissions 2015 based on fuel sold.

Figure 53: Spatial distribution of Austria´s NOx emissions 2015 based on fuel used.



9.1.4.2 Spatial distribution of SO2 emissions in 2015

Figure 54: Spatial distribution of Austria´s SO2 emissions 2015 based on fuel sold.

9.1.4.3 Spatial distribution of NMVOC emissions in 2015

Figure 55: Spatial distribution of Austria´s NMVOC emissions 2015 based on fuel sold.



9.1.4.4 Spatial distribution of NH3 emissions in 2015

Figure 56: Spatial distribution of Austria´s NH3 emissions 2015 based on fuel sold.

9.1.4.5 Spatial distribution of PM2.5 emissions in 2015

Figure 57: Spatial distribution of Austria´s PM2.5 emissions 2015 based on fuel sold.



9.2 Large Point Sources (LPS)

“Large point sources” (LPS) are defined as facilities whose combined emissions, within the lim-ited identifiable area of the site premises, exceed the pollutant emission thresholds identified in Table 1 of the revised 2014 CLRTAP Reporting Guidelines. These thresholds have been ex-tracted from the full list of pollutants in Regulation (EC) No. 166/2006 concerning the establish-ment of a European Pollutant Release and Transfer Register.

Austria reported 55 LPS for the year 2015. The data is distributed to the following GNFR sectors: 11 LPS in GNFR sector A_PublicPower 35 LPS in GNFR sector B_Industry 1 LPS in GNFR sector D_Fugitive 5 LPS in GNFR sector E_Solvents 3 LPS in GNFR sector I_Offroad

9.2.1 Activity Data

Emission values taken for LPS of 2015 are reported by Austrian plants according to Directive 2010/75/EU on industrial emissions (integrated pollution prevention and control) (Large Com-bustion Plants – LCP) as well as under Regulation (EC) No 166/2006 on the establishment of a European Pollutant Release and Transfer Register. The data for 2015 was taken from Austria´s official submissions on 31st of March 2017.

Emissions from LCPs are available on installation level; E-PRTR data is reported on facility level (one or more installations on the same site operated by the same natural or legal person). So, it was necessary to sum up the respective LCP installations for comparison with the related E-PRTR facility. In case of differences between LCP emissions and E-PRTR emissions the upper emission value was taken. In the following table an overview of the required information and the respective data source is presented.

Table 333: Overview of data sources for LPS (required in ANNEX VI).

Activity data Data source

LPS Facility name according to E-PRTR reporting

GNFR Expert judgement

PRTR Facility ID PRTR ID according to E-PRTR reporting

Height Class (1-5) Height Class according to LCP reporting*

Longitude/latitude Longitude/latitude according to E-PRTR reporting

*If there were more than one height classes available, the upper value was taken.




The applied methodology is in accordance with the revised 2014 CLRTAP Reporting Guide-lines. The Austrian LPS data is prepared in line with the list of pollutants to be reported if the applicable threshold value is exceeded as demonstrated in Table 1 of the CLRTAP Reporting Guidelines. Finally, the activity data (E-PRTR data and LCP data) was matched for each rele-vant NFR sector and aggregated as required in ANNEX VI (Template for LPS data for each rel-evant aggregated Gridding NFR sectors (GNFR)).

PM emissions

Under Directive 2010/75/EU on industrial emissions (IED) PM2.5 and PM10 emissions are not re-ported separately, but as total dust emissions. TSP (total suspended particles) was assumed to represent the total dust emissions. PM2.5 and PM10 emissions were calculated as fractions of TSP in line with the Austrian Air Emission Inventory.

PM2.5 emissions are also not reported under the E-PRTR Regulation. However, PM10 emissions are submitted under E-PRTR, and so PM2.5 could be calculated based on the sectoral composi-tion of TSP and PM10 as described before.

9.3 Recalculations

No recalculations for gridded data and LPS have been carried out since last submission in 2012. In 2017 data for 2015 only was reported.

9.4 Planned Improvements

Currently, no improvements are planned.

Austria’s Informative Inventory Report (IIR) 2020 – References


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UMWELTBUNDESAMT (2000c): Lahl, U.; Zeschmar-Lahl, B. & Angerer, T.: Entwicklungspotentiale der mechanisch-biologischen Abfallbehandlung. Eine ökologische Analyse. Wien

UMWELTBUNDESAMT (2001a): Emissionsfaktoren als Grundlage für die Österreichische Luftschadstoff-Inventur. Stand 1999. Interner Bericht, Bd. IB-614. Umweltbundesamt, Wien.

UMWELTBUNDESAMT (2001b): Häusler, G.: Emissionen aus Abfalldeponien 1980–1998, Interner Bericht, Bd. IB-623. Umweltbundesamt, Wien.

UMWELTBUNDESAMT (2001c): Wiesenberger, H.: State-of-the-art for the production of nitric acid with regard to the IPPC directive. Monographien, Bd. M-150. Umweltbundesamt, Wien.

UMWELTBUNDESAMT (2001d): Grech, H. & Rolland, C.: Stand der Abfallbehandlung in Österreich im Hinblick auf das Jahr 2004. Berichte, Bd. BE-182. Umweltbundesamt, Wien.

UMWELTBUNDESAMT (2003b): Böhmer, S.; Schindler, I. & Szednyj, I.: Stand der Technik bei Kalorischen Kraftwerken und Referenzanlagen in Österreich. Monographien, Bd. M-162. Umweltbundesamt, Wien.

UMWELTBUNDESAMT (2003c): Rolland, C. & Scheibengraf, M.: Biologisch abbaubarer Kohlenstoff im Restmüll. Berichte, Bd. BE-236. Umweltbundesamt, Wien.

UMWELTBUNDESAMT (2004a): Wieser, M. & Kurzweil, A.: Emissionsfaktoren als Grundlage für die Österreichische Luftschadstoffinventur Stand 2003. Berichte, Bd. BE-254. Umweltbundesamt, Wien.

UMWELTBUNDESAMT (2004b): Rolland, C. & Oliva, J.: Erfassung von Deponiegas – Statusbericht von österreichischen Deponien. Berichte, Bd. BE-238. Umweltbundesamt, Wien.

UMWELTBUNDESAMT (2004c): Schindler, I.; Kutschera, U. & Wiesenberger, H.: Medienübergreifende Umweltkontrolle in ausgewählten Gebieten. Umweltbundesamt, Wien.



UMWELTBUNDESAMT (2005a): Stubenvoll, J.; Holzerbauer, E.; Böhmer, S. et al.: Technische Maßnahmen zur Minderung der Staub- und NOx-Emissionen bei Wirbelschichtkesseln und Laugenverbrennungskesseln. Umweltbundesamt, Wien.

UMWELTBUNDESAMT (2005b): Schachermayer, E.: Vergleich und Evaluierung verschiedener Modelle zur Berechnung der Methanemissionen aus Deponien. Umweltbundesamt, Wien 2005. (not published).

UMWELTBUNDESAMT (2006a): Gager, M.: Emissionen Österreichischer Großfeuerungsanlagen 1990–2004. Reports, Bd. REP-0006. Umweltbundesamt, Wien.

UMWELTBUNDESAMT (2006b): Krutzler, T.; Böhmer, S.; Szednyj, I.; Wiesenberger, H. & Poupa, S.: NOx-Emissionen 2003–2020. Emissionsprognose und Minderungspotenziale für Energieumwandlung und ausgewählte industrielle Sektoren. Report, Bd. REP-0040. Umweltbundesamt, Wien. (unpublished).

UMWELTBUNDESAMT (2006c): Salchenegger, S.: Biokraftstoffe im Verkehrssektor in Österreich 2006, Zusammenfassung der Daten der Republik Österreich gemäß Art. 4, Abs. 1 der Richtlinie 2003/30/EG für das Berichtsjahr 2005. Reports, Bd. REP-0068. Umweltbundesamt, Wien.

UMWELTBUNDESAMT (2007): Böhmer, S.; Fröhlich, M.; Köther, T.; Krutzler, T.; Nagl, C.; Pölz, W.; Poupa, S.; Rigler, E.; Storch, A. & Thanner, G.: Aktualisierung von Emissionsfaktoren als Grundlage für den Anhang des Energieberichts. Reports, Bd. REP-0075. Umweltbundesamt, Wien.

UMWELTBUNDESAMT (2008): Schachermayer, E. & Lampert, C.: Deponiegaserfassung auf österreichischen Deponien. Reports, Bd. REP-0100. Umweltbundesamt, Wien.

UMWELTBUNDESAMT (2011): Data on sewage sludge application provided by the provincial governments. Vienna 2011.

UMWELTBUNDESAMT (2010, 2014 & 2018): External review of the Agricultural calculation model by Austrian Agricultural experts within the framework of stakeholder meetings held in 2010, 2014 & 2018. Discussion and validation of applied values, parameters and time series by the national experts. Vienna.

UMWELTBUNDESAMT (2012): National Action Plan pursuant to Article 5 of the Stockholm Convention on POPs and Article 6 of the EU-POP Regulation. First review, 2012. Report, REP-0395, Umweltbundesamt, Wien.


UMWELTBUNDESAMT (2014a): Data on sewage sludge application provided by the provincial governments. Vienna 2014.

UMWELTBUNDESAMT (2014b): LAMPERT, C.: Stand der temporären Abdeckung von Deponien und Deponiegaserfassung. Bericht. REP-0484. Umweltbundesamt, Wien.

UMWELTBUNDESAMT (2014c): Haider, S.; Anderl, M.; Jobstmann, H.; Köther, T.; Lampert, C.; Moosmann, L.; Pazdernik, K.; Pinterits, M.; Poupa, S.; Stranner, G. & Zechmeister, A.: Austria’s Informative Inventory Report 2014. Submission under the UNECE Convention on Long-range Transboundary Air Pollution. Reports, Bd. REP-0474 Umweltbundesamt, Wien.





UMWELTBUNDESAMT (2016b): Lampert, C.; Neubauer, M. & Bernhardt A.: Kommunale Grünabfälle (KoGa). Report. unpublished. Vienna.


UMWELTBUNDESAMT (2017b): Zechmeister, A.; Anderl, M.; Haider, S.; Krutzler, T.; Lampert, C.; Pazdernik, K.; Poupa, S.; Purzner, M.; Schieder, W.; Storch, A. & Stranner, G.: Austria’s National Air Emission Projections 2017 for 2020, 2025 and 2030, Bd. REP-0611. Umweltbundesamt, Wien 2017.

UMWELTBUNDESAMT (2017c): Böhmer, S.; Klösch, N.; Schieder, W.; Storch, A. & Thielen, P.: Emissionsfaktoren Raumwärme II. Endbericht zum AVH 03049-014. (unveröffentlicht).



UMWELTBUNDESAMT (2020a): Pazdernik, K..; Anderl, M.; Friedrich, A.; Gangl, M.; Haider, S.; Köther, T.; Kriech, M.; Lampert, C.; Matthews, B.; Pfaff, G.; Pinterits, M.; Poupa, S.; Purzner, M.; Schieder, W.; Schmid, C.; Schmidt, G.; Schodl, B.; Schwaiger, E.; Schwarzl, B.; Titz, M.; Weiss, P. & Zechmeister, A.: Austria's National Inventory Report 2020. Submission under the United Nations Framework Convention on Climate Change and under the Kyoto Protocol. Reports, REP-0724. Umweltbundesamt. Vienna 2020.

UMWELTBUNDESAMT (2020b) Preliminary data on connection rate 2018 based on information reported by Vienna and Tyrol.

UMWELTBUNDESAMT (2019b) Lampert, C. & Thaler, P.: Deponiegaserfassung 2013–2017. Reports REP-0679. Wien 2019.

UMWELTBUNDESAMT (2019c): Stoiber, H.; Kellner, M. & Schindler, I.: Stand der Technik Österreichischer Abfallverbrennungsanlagen, Statusbericht 2016, Wien 2018.

UMWELTBUNDESAMT (2019d): Titz, M.; Anderl, M.; Haider, S.; Krutzler, T.; Lampert,; Poupa, S.; Purzner, M.; Schieder, W.; Storch, A., Stranner & G. Zechmeister, A.: Austria’s National Air Emission Projections 2017 for 2020, 2025 and 2030, Bd. REP-Draft. Umweltbundesamt, Wien 2019.

UMWELTBUNDESAMT (2020): Preliminary data on connection rate 2018 based on information reported by Vienna and Tyrol.

UMWELTBUNDESAMT BERLIN (UBA) (1998): Ermittlung von Emissionen und Minderungsmaßnahmen für POPs in Deutschland. UBA-Texte 74/98, Berlin.

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http://www.unece.org/environmental-policy/conventions/envlrtapwelcome/publications.html

http://www.unece.org/environmental-policy/conventions/envlrtapwelcome/publications.html



UNTERARBEITSGRUPPE N-ADHOC (2004): Überprüfung und Überarbeitung der N-Anfallswerte für einzelne Tierkategorien. Unterlagen ausgearbeitet vom Fachbeirat für Bodenfruchtbarkeit und Bodenschutz des BMLFUW.

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WINDSPERGER, A.; MAYR, B.; SCHMIDT-STEJSKAL, H.; ORTHOFER, R. & WINIWARTER, W. (1999): Entwicklung der Schwermetallemissionen – Abschätzung der Emissionen von Blei, Cadmium und Quecksilber für die Jahre 1985, 1990 und 1995 gemäß der CORINAIR-Systematik. Institut für Industrielle Ökologie und Österreichisches Forschungszentrum Seibersdorf, Wien. (not published).

WINDSPERGER, A.; SCHMIDTH-STEJSKAL, H. & STEINLECHNER, S. (2003): Erhebung der IST-Situation und der Struktur der NOx-Emissionen für bestimmte Sektoren der Industrie und Erstellung eines Maßnahmenplanes zur Reduktion der NOx-Emissionen bis 2010. Institut für Industrielle Ökologie, St. Pölten.

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SCHÖRNER, G. (2004): Studie zur Anpassung der Zeitreihe der Lösungsmittelemissionen der österreichischen Luftschadstoffinventur (OLI) 1980–2002. Institut für Industrielle Ökologie (IIÖ) und Forschungsinstitut für Energie und Umweltplanung. Wirtschaft- und Marktanalysen GmbH (FIEU). Studie im Auftrag des Umweltbundesamt, Wien.

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WINDSPERGER, A.; STEJSKAL, H.; PURZNER, M.; TITZ, M. & BURGSTALLER, J. (2018): Dokumentation der methodischen Arbeiten zur VOC-Inventur in Österreich. Internal Report. Vienna 2018.

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WINIWARTER, W. (2007): Quantifying Uncertainties of the Austrian Greenhouse Gas Inventory, ARC (Austrian Research Centers) Seibersdorf. Research Report ARC-sys-0154. Final report contracted by Umweltbundesamt.

WINIWARTER, W.; BAUER, H.; CASEIRO, A. & PUXBAUM, H. (2009): Quantifying emissions of Primary Biological Aerosol Particle mass in Europe. Atmos. Environ. 43, 1403–1409 (2009).

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WINIWARTER, W. & SCHNEIDER, M. (1995): Abschätzung der Schwermetallemissionen in Österreich. Reports, Bd. UBA-95-108. Umweltbundesamt, Wien.

WINIWARTER, W.; TRENKER, C. & HÖFLINGER, W. (2001): Österreichische Emissionsinventur für Staub. Österreichisches Forschungszentrum Seibersdorf, Wien.

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ZAR – Zentrale Arbeitsgemeinschaft österreichischer Rinderzüchter (2004): Cattle Breeding in Austria. 148pp.

ZESSNER, M. (1999): Bedeutung und Steuerung von Nährstoff- und Schwermetallflüssen des Abwassers. Wiener Mitteilung Band 157. Wien.

Energy demand model for space heating

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STATCUBE (2014a): Neue Gebäude mit Wohnungen 1970 - 1979; ohne An-, Auf-, Umbautätigkeit (Wohnbaustatistik). Statistische Datenbank von Statistik, Wien.

STATCUBE (2014b): Neue Gebäude mit Wohnungen 1980 - 2002; ohne An-, Auf-, Umbautätigkeit (Wohnbaustatistik). Statistische Datenbank von Statistik, Wien.

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STATCUBE (2019a): Bevölkerung zu Jahresbeginn ab 1982 (Bevölkerungsstatistik). Statistische Datenbank von Statistik, Wien.

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UMWELTBUNDESAMT (2014): Schieder, W.; Storch, A..; Thielen, P.; Wampl, S. & Zechmeister, A.: Entwicklung eines Raumwärme-Emissionsmodells. Endbericht (unveröffentlicht). Erstellung im Auftrag des BMLFUW, Umweltbundesamt, Wien, Dezember 2014.

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Austria’s Informative Inventory Report (IIR) 2020 – Abbreviations


11 ABBREVIATIONS

AMA ...................... Agrarmarkt Austria

ASFINAG .............. Autobahnen- und Schnellstraßen-Finanzierungs-Aktiengesellschaft

BAWP ................... Bundes-Abfallwirtschaftsplan (Federal Waste Management Plan)

BLI ........................ Austrian Air Emission Inventory on federal level (“Bundesländer Luftschadstoff-inventur”)

BMDW .................. Bundesministerium für Digitalisierung und Wirtschaftsstandort (Federal Ministry for Digital and Economic Affairs)

BMK ...................... Bundesministerium für Klimaschutz, Umwelt, Energie, Mobilität, Innovation & Techno-logie; (Federal Ministry of Climate Action, Environment, Energy, Mobility, Innovation and Technology) (formerly BMNT)

BMLFUW .............. Bundesministerium für Land- und Forstwirtschaft, Umwelt und Wasserwirtschaft (Federal Ministry for Agriculture, Forestry, Environment and Water Management), from 2018 on BMNT

BMNT .................... Bundesministerium für Nachhaltigkeit und Tourismus (Federal Ministry of Sustainability and Tourism), until 2017 BMLFUW

BMUJF .................. Bundesministerium für Umwelt, Jugend und Familie (Federal Ministry for Environment, Youth and Family (before 2000)

BUWAL ................. Bundesamt für Umwelt, Wald und Landschaft. Bern (The Swiss Agency for the Environment, Forests and Landscape (SAEFL), Bern)

CAN ...................... Calcium Ammonium Nitrate (Fertilizer)

CORINAIR ............ Core Inventory Air

CORINE ................ Coordination d´information Environmentale

CRF ...................... Common Reporting Format

DKDB .................... Dampfkesseldatenbank (Austrian annual steam boiler inventory)

EC ......................... European Community

EDM ...................... Electronic Data Management

EEA ....................... European Environment Agency

EIONET ................ European Environment Information and Observation NETwork

EMEP .................... Cooperative Programme for Monitoring and Evaluation of the Long-range Transmission of Air Pollutants in Europe

ETS ....................... Emission Trading System

EPER .................... European Pollutant Emission Register

E-PRTR ................ European Pollutant Release and Transfer Register

GDP ...................... Gross Domestic Product

GLOBEMI ............. Globale Modellbildung für Emissions- und Verbrauchsszenarien im Verkehrssektor ((Global Modelling for Emission- and Fuel consumption Scenarios of the Transport Sector) see (Hausberger 1998))

GPG ...................... Good Practice Guidance (of the IPCC)

HBEFA .................. “Handbook of Emission Factors”

HM ........................ Heavy Metals

IEA ........................ International Energy Agency



IEF ........................ Implied emission factor

IFR ........................ Instrument Flight Rules

IIR ......................... Informative Inventory Report

IPCC ..................... Intergovernmental Panel on Climate Change

LTO ....................... Landing/Take-Off cycle

MCF ...................... Methane Conversion Factor

MEET .................... MEET – Methodology for calculating transport emissions and energy consumption

MMS ..................... Manure Management System

NACE .................... Nomenclature des activites economiques de la Communaute Europeenne

NAPFUE ............... Nomenclature for Air Pollution Fuels

NEC ...................... National Emissions Ceiling (Directive (EU) 2016/2284 on the reduction of national emissions of certain atmospheric pollutants – NEC Directive)

NEMO ................... Network Emission Model

NFR ...................... Nomenclature for Reporting (Format of Reporting under the UNECE/LRTAP Convention)

NIR ........................ National Inventory Report (Submission under the United Nations Framework Convention on Climate Change)

NISA ..................... National Inventory System Austria

NPK.......................Nitrogen (N) Phosphorus (P) and Potassium (K) (Fertilizer)

OECD ................... Organisation for Economic Co-operation and Development

ODS ...................... Ozone depleting substances

OLI ........................ Österreichische Luftschadstoff (Inventur Austrian Air Emission Inventory)

PM ........................ Particulate Matter

POPs .................... Persistent Organic Pollutants

PRTR .................... Pollutant Release and Transfer Register

QA/QC .................. Quality Assurance/Quality Control

QMS ...................... Quality Management System

RWA ..................... Raiffeisen Ware Austria (see www.rwa.at)

SNAP .................... Selected Nomenclature on Air Pollutants

SOP ...................... Standard Operation Procedure

TAN ....................... Total ammoniacal nitrogen

Umweltbundesamt..Environment Agency Austria

UNECE/LRTAP ..... United Nations Economic Commission for Europe.Convention on Long-range Transboundary Air Pollution

UNFCCC ............... United Nations Framework Convention on Climate Change

VFR ....................... Visual Flight Rules

VRF ....................... Variable Refrigerant Flow

VMOe .................... Verkehrs-Mengenmodell-Oesterreich

WIFO .................... Wirtschaftsforschungsinstitut (Austrian Institute for Economic Research)



Chemical Symbols

Symbol ................ Name

Greenhouse gases

CH4 ..................... Methane CO2 ..................... Carbon Dioxide N2O ..................... Nitrous Oxide HFCs .................. Hydroflurocarbons PFCs ................... Perfluorocarbons SF6 ..................... Sulphur hexafluoride NF3……………...Nitrogen Trifluoride Further chemical compounds

CO ..................... Carbon Monoxide Cd ..................... Cadmium NH3 ..................... Ammonia Hg ..................... Mercury NOx ..................... Nitrogen Oxides (NO plus NO2) NO2 ..................... Nitrogen Dioxide NMVOC .............. Non-Methane Volatile Organic Compounds PAH .................... Polycyclic Aromatic Hydrocarbons Pb ..................... Lead POP .................... Persistent Organic Pollutants SO2 ..................... Sulfur Dioxide SOx ..................... Sulfur Oxides Units and Metric Symbols

UNIT Name Unit for Metric Symbol Prefix Factor

g gram mass P peta 1015

t ton mass T tera 1012

W watt power G giga 109

J joule calorific value M mega 106

m meter length k kilo 103

h hecto 102

Mass Unit Conversion da deca 101

1g d deci 10-1

1kg = 1 000 g c centi 10-2

1t = 1 000 kg = 1 Mg m milli 10-3

1kt = 1 000 t = 1 Gg µ micro 10-6

1Mt = 1 Mio t = 1 Tg n nano 10-9

Austria’s Informative Inventory Report (IIR) 2020 – Appendix


12 Appendix

12.1 Emission Trends per Sector – Submission under UNECE/LRTAP

Table A-1: Emission trends for SO2 [kt] 1990–2018 – Submission under UNECE/LRTAP.

SO2 NFR Sectors 1 1.A 1.B 2 3 5 6

ENER

GY

FUEL

CO

MB

UST

ION

A

CTI

VITI

ES

FUG

ITIV

E EM

ISSI

ON

S FR

OM

FU

ELS

IND

UST

RIA

L PR

OC

ESSE

S an

d PR

OD

UC

T U

SE

AG

RIC

ULT

UR

E

WA

STE

OTH

ER E

MIS

SIO

N

SOU

RC

ES

NA

TIO

NA

L TO

TAL

Inte

rnat

iona

l B

unke

rs

1990 71.69 69.69 2.00 1.93 0.01 0.07 NO 73.70 0.26

1991 69.05 67.75 1.30 1.61 0.00 0.06 NO 70.72 0.29

1992 52.79 50.79 2.00 1.36 0.00 0.04 NO 54.19 0.31

1993 51.66 49.56 2.10 1.11 0.00 0.04 NO 52.82 0.33

1994 46.02 44.74 1.28 1.12 0.00 0.05 NO 47.19 0.34

1995 45.69 44.16 1.53 1.07 0.01 0.05 NO 46.81 0.38

1996 42.89 41.69 1.20 0.99 0.00 0.05 NO 43.93 0.43

1997 39.38 39.31 0.07 0.96 0.00 0.05 NO 40.40 0.44

1998 34.70 34.66 0.04 0.87 0.00 0.06 NO 35.63 0.46

1999 32.87 32.82 0.04 0.81 0.01 0.06 NO 33.74 0.45

2000 30.74 30.69 0.04 0.78 0.00 0.06 NO 31.58 0.48

2001 31.68 31.64 0.05 0.71 0.01 0.06 NO 32.46 0.47

2002 30.62 30.58 0.04 0.71 0.01 0.06 NO 31.39 0.43

2003 30.40 30.36 0.05 0.71 0.00 0.06 NO 31.17 0.40

2004 25.81 25.77 0.04 0.72 0.01 0.06 NO 26.60 0.47

2005 25.17 25.13 0.04 0.72 0.00 0.06 NO 25.95 0.55

2006 26.01 25.96 0.05 0.73 0.00 0.05 NO 26.79 0.58

2007 22.65 22.60 0.05 0.75 0.00 0.04 NO 23.44 0.61

2008 19.51 19.47 0.04 0.78 0.00 0.03 NO 20.33 0.61

2009 14.07 14.02 0.06 0.70 0.00 0.02 NO 14.80 0.53

2010 15.32 15.27 0.05 0.70 0.00 0.01 NO 16.04 0.57

2011 14.53 14.49 0.05 0.68 0.00 0.01 NO 15.23 0.60

2012 14.20 14.16 0.05 0.65 0.00 0.01 NO 14.86 0.57

2013 13.84 13.80 0.04 0.59 0.00 0.01 NO 14.44 0.54

2014 13.98 13.94 0.04 0.55 0.00 0.01 NO 14.54 0.54

2015 13.40 13.36 0.04 0.57 0.00 0.01 NO 13.98 0.58

2016 12.74 12.71 0.02 0.57 0.00 0.01 NO 13.32 0.54

2017 12.26 12.22 0.04 0.57 0.00 0.01 NO 12.84 0.52

2018 11.18 11.16 0.02 0.57 0.00 0.01 NO 11.77 0.59



Table A-2: Emission trends for NOx [kt] 1990–2018 – Submission under UNECE/LRTAP.

NOx NFR Sectors 1 1.A 1.B 2 3 5 6

ENER

GY

FUEL

C

OM

BU

STIO

N

AC

TIVI

TIES

FUG

ITIV

E EM

ISSI

ON

S FR

OM

FU

ELS

IND

UST

RIA

L PR

OC

ESSE

S an

d PR

OD

UC

T U

SE

AG

RIC

ULT

UR

E

WA

STE

OTH

ER E

MIS

SIO

N

SOU

RC

ES

NA

TIO

NA

L TO

TAL

Inte

rnat

iona

l

Bun

kers

1990 200.79 200.79 IE 4.27 12.05 0.10 NO 217.22 2.44

1991 210.73 210.73 IE 3.93 11.99 0.09 NO 226.75 2.76

1992 199.51 199.51 IE 4.02 11.73 0.06 NO 215.32 3.00

1993 193.70 193.70 IE 1.46 11.57 0.05 NO 206.77 3.18

1994 185.71 185.71 IE 1.38 11.43 0.05 NO 198.56 3.31

1995 185.33 185.33 IE 0.90 11.61 0.05 NO 197.88 3.73

1996 203.27 203.27 IE 0.87 11.50 0.05 NO 215.68 4.14

1997 189.42 189.42 IE 0.86 11.57 0.05 NO 201.89 4.29

1998 201.18 201.18 IE 0.83 11.62 0.05 NO 213.68 4.43

1999 193.29 193.29 IE 0.82 11.27 0.05 NO 205.43 4.33

2000 199.14 199.14 IE 0.83 11.08 0.05 NO 211.10 6.44

2001 209.94 209.94 IE 0.78 11.05 0.05 NO 221.81 6.32

2002 217.78 217.78 IE 0.79 11.07 0.05 NO 229.69 5.67

2003 229.45 229.45 IE 0.81 10.59 0.05 NO 240.90 5.21

2004 229.79 229.79 IE 0.69 10.06 0.05 NO 240.59 6.09

2005 235.27 235.27 IE 0.70 10.12 0.05 NO 246.14 6.99

2006 225.30 225.30 IE 0.58 10.16 0.04 NO 236.09 7.54

2007 217.73 217.73 IE 0.48 10.31 0.04 NO 228.56 7.99

2008 203.63 203.63 IE 0.56 10.90 0.03 NO 215.12 7.90

2009 189.97 189.97 IE 0.41 10.69 0.02 NO 201.09 6.86

2010 191.80 191.80 IE 0.55 9.78 0.02 NO 202.15 7.60

2011 183.20 183.20 IE 0.52 10.28 0.02 NO 194.02 7.98

2012 177.91 177.91 IE 0.55 10.40 0.02 NO 188.87 7.68

2013 177.30 177.30 IE 0.45 10.29 0.02 NO 188.07 7.46

2014 168.35 168.35 IE 0.46 10.60 0.02 NO 179.43 7.49

2015 164.84 164.84 IE 0.52 10.99 0.02 NO 176.36 8.18

2016 158.59 158.59 IE 0.52 11.17 0.02 NO 170.30 10.28

2017 150.47 150.47 IE 0.47 10.99 0.02 NO 161.95 10.06

2018 139.68 139.68 IE 0.41 10.75 0.02 NO 150.86 11.54



Table A-3: Emission trends for NMVOC [kt] 1990–2018 – Submission under UNECE/LRTAP.

NMVOC NFR Sectors 1 1.A 1.B 2 3 5 6

ENER

GY

FUEL

C

OM

BU

STIO

N

AC

TIVI

TIES

FUG

ITIV

E EM

ISSI

ON

S FR

OM

FU

ELS

IND

UST

RIA

L PR

OC

ESSE

S an

d PR

OD

UC

T U

SE

AG

RIC

ULT

UR

E

WA

STE

OTH

ER E

MIS

SIO

N

SOU

RC

ES

NA

TIO

NA

L TO

TAL

Inte

rnat

iona

l

Bun

kers

1990 163.13 147.64 15.49 118.54 52.19 0.16 NO 334.02 0.18

1991 164.92 149.80 15.12 112.01 51.21 0.16 NO 328.31 0.20

1992 150.76 135.58 15.19 105.25 48.54 0.15 NO 304.70 0.22

1993 138.71 124.06 14.65 98.55 47.26 0.15 NO 284.67 0.24

1994 123.30 112.18 11.12 91.99 46.79 0.14 NO 262.22 0.25

1995 114.91 105.43 9.49 85.28 46.25 0.14 NO 246.57 0.29

1996 108.25 99.78 8.46 83.72 45.10 0.13 NO 237.20 0.34

1997 96.18 88.22 7.95 82.37 44.33 0.13 NO 223.01 0.37

1998 89.40 82.97 6.43 81.06 43.99 0.13 NO 214.58 0.40

1999 81.77 76.10 5.67 78.32 43.28 0.12 NO 203.49 0.39

2000 75.26 69.57 5.69 62.15 42.27 0.12 NO 179.79 0.42

2001 72.20 68.36 3.84 59.96 41.82 0.11 NO 174.09 0.41

2002 68.78 64.75 4.03 59.11 40.94 0.11 NO 168.94 0.37

2003 66.65 62.70 3.96 58.53 40.44 0.11 NO 165.74 0.34

2004 62.76 59.19 3.57 49.80 40.16 0.11 NO 152.83 0.40

2005 60.18 56.84 3.34 57.32 39.50 0.11 NO 157.11 0.47

2006 56.69 53.34 3.36 63.26 39.19 0.10 NO 159.25 0.50

2007 53.70 50.71 2.98 61.94 39.07 0.10 NO 154.80 0.53

2008 51.34 48.59 2.75 58.71 38.79 0.10 NO 148.94 0.52

2009 48.55 45.97 2.59 47.89 38.98 0.09 NO 135.51 0.45

2010 50.05 47.59 2.45 46.70 38.58 0.09 NO 135.41 0.49

2011 45.90 43.49 2.41 46.03 37.92 0.08 NO 129.93 0.51

2012 45.60 43.20 2.40 44.13 37.61 0.08 NO 127.42 0.49

2013 45.04 42.73 2.30 38.87 37.58 0.07 NO 121.56 0.46

2014 40.12 37.71 2.42 36.81 37.63 0.07 NO 114.63 0.46

2015 40.57 38.25 2.32 33.37 37.43 0.06 NO 111.44 0.50

2016 39.92 37.65 2.27 32.33 37.42 0.06 NO 109.73 0.23

2017 39.40 37.12 2.29 33.96 37.31 0.06 NO 110.73 0.20

2018 36.56 34.39 2.17 33.63 36.97 0.06 NO 107.22 0.22



Table A-4: Emission trends for NH3 [kt] 1990–2018 – Submission under UNECE/LRTAP.

NH3 NFR Sectors 1 1.A 1.B 2 3 5 6

ENER

GY

FUEL

C

OM

BU

STIO

N

AC

TIVI

TIES

FUG

ITIV

E EM

ISSI

ON

S FR

OM

FU

ELS

IND

UST

RIA

L PR

OC

ESSE

S an

d PR

OD

UC

T U

SE

AG

RIC

ULT

UR

E

WA

STE

OTH

ER E

MIS

SIO

N

SOU

RC

ES

NA

TIO

NA

L TO

TAL

Inte

rnat

iona

l

Bun

kers

1990 1.962 1.962 IE 0.339 59.063 0.367 NO 61.731 0.002

1991 2.432 2.432 IE 0.577 59.181 0.382 NO 62.573 0.002

1992 2.616 2.616 IE 0.438 57.588 0.434 NO 61.076 0.002

1993 2.898 2.898 IE 0.287 58.370 0.515 NO 62.070 0.002

1994 3.038 3.038 IE 0.236 58.121 0.622 NO 62.016 0.002

1995 3.226 3.226 IE 0.165 59.076 0.642 NO 63.109 0.003

1996 3.404 3.404 IE 0.163 58.223 0.668 NO 62.458 0.003

1997 3.469 3.469 IE 0.162 58.435 0.666 NO 62.733 0.003

1998 3.772 3.772 IE 0.168 58.476 0.697 NO 63.114 0.003

1999 3.802 3.802 IE 0.186 57.153 0.767 NO 61.908 0.003

2000 3.755 3.755 IE 0.167 55.838 0.822 NO 60.581 0.003

2001 3.922 3.922 IE 0.146 55.670 0.922 NO 60.659 0.003

2002 4.048 4.048 IE 0.128 54.794 1.018 NO 59.987 0.003

2003 4.158 4.158 IE 0.141 54.673 1.099 NO 60.071 0.003

2004 4.045 4.045 IE 0.122 54.429 1.346 NO 59.942 0.003

2005 4.010 4.005 0.005 0.127 54.292 1.444 NO 59.873 0.004

2006 3.935 3.928 0.006 0.136 54.789 1.470 NO 60.329 0.004

2007 3.847 3.841 0.005 0.138 56.149 1.515 NO 61.648 0.004

2008 3.585 3.582 0.003 0.140 56.051 1.535 NO 61.311 0.004

2009 3.388 3.385 0.003 0.148 57.623 1.571 NO 62.731 0.004

2010 3.435 3.432 0.003 0.153 57.538 1.565 NO 62.690 0.004

2011 3.136 3.134 0.002 0.160 57.273 1.563 NO 62.132 0.004

2012 2.999 2.998 0.001 0.153 57.672 1.584 NO 62.409 0.004

2013 2.837 2.837 0.001 0.155 57.961 1.532 NO 62.485 0.004

2014 2.604 2.603 0.001 0.148 58.896 1.579 NO 63.227 0.004

2015 2.640 2.639 0.000 0.140 59.621 1.611 NO 64.011 0.004

2016 2.565 2.565 0.000 0.146 60.505 1.598 NO 64.815 0.004

2017 2.598 2.598 0.000 0.167 61.300 1.602 NO 65.666 0.004

2018 2.537 2.537 0.001 0.135 60.358 1.601 NO 64.631 0.005



Table A-5: Emission trends for CO [kt] 1990–2018 – Submission under UNECE/LRTAP.

CO NFR Sectors 1 1.A 1.B 2 3 5 6

ENER

GY

FUEL

C

OM

BU

STIO

N

AC

TIVI

TIES

FUG

ITIV

E EM

ISSI

ON

S FR

OM

FU

ELS

IND

UST

RIA

L PR

OC

ESSE

S an

d PR

OD

UC

T U

SE

AG

RIC

ULT

UR

E

WA

STE

OTH

ER E

MIS

SIO

N

SOU

RC

ES

NA

TIO

NA

L TO

TAL

Inte

rnat

iona

l

Bun

kers

1990 1 200.68 1 200.68 IE 37.19 1.23 10.31 NO 1 249.41 0.49

1991 1 212.40 1 212.40 IE 32.45 1.20 10.51 NO 1 256.55 0.55

1992 1 152.76 1 152.76 IE 35.31 1.21 10.36 NO 1 199.64 0.59

1993 1 089.17 1 089.17 IE 37.01 1.09 10.26 NO 1 137.53 0.63

1994 1 022.32 1 022.32 IE 38.14 1.18 9.95 NO 1 071.60 0.66

1995 922.40 922.40 IE 34.72 1.17 9.46 NO 967.74 0.75

1996 923.30 923.30 IE 29.08 1.12 8.93 NO 962.42 0.84

1997 850.10 850.10 IE 28.21 1.19 8.52 NO 888.02 0.89

1998 807.43 807.43 IE 25.85 1.16 8.19 NO 842.63 0.93

1999 695.34 695.34 IE 21.76 1.19 7.85 NO 726.15 0.89

2000 694.43 694.43 IE 18.69 1.05 7.52 NO 721.69 0.80

2001 672.11 672.11 IE 14.55 1.17 7.21 NO 695.04 0.78

2002 641.37 641.37 IE 14.42 1.10 7.19 NO 664.09 0.66

2003 643.89 643.89 IE 14.34 1.05 7.18 NO 666.46 0.65

2004 626.14 626.14 IE 14.55 1.63 7.30 NO 649.61 0.73

2005 602.20 602.20 IE 14.53 0.98 6.88 NO 624.59 0.91

2006 602.26 602.26 IE 14.71 0.91 6.53 NO 624.41 0.92

2007 579.25 579.25 IE 14.89 0.93 6.16 NO 601.23 0.96

2008 560.39 560.39 IE 14.82 0.90 5.85 NO 581.96 0.96

2009 541.18 541.18 IE 13.88 0.84 5.44 NO 561.34 0.82

2010 557.23 557.23 IE 14.28 0.80 5.09 NO 577.39 0.87

2011 540.45 540.45 IE 14.30 0.59 4.76 NO 560.10 0.86

2012 540.67 540.67 IE 14.14 0.43 4.47 NO 559.71 0.83

2013 545.35 545.35 IE 14.29 0.39 4.16 NO 564.19 0.74

2014 510.15 510.15 IE 14.19 0.44 3.85 NO 528.63 0.74

2015 523.38 523.38 IE 14.20 0.38 3.61 NO 541.56 0.78

2016 519.98 519.98 IE 14.12 0.38 3.36 NO 537.84 1.49

2017 511.43 511.43 IE 14.14 0.35 3.15 NO 529.08 1.46

2018 472.56 472.56 IE 14.22 0.35 2.96 NO 490.09 1.73



Table A-6: Emission trends for Cd [kg] 1990–2018 – Submission under UNECE/LRTAP.

Cd NFR Sectors 1 1.A 1.B 2 3 5 6

ENER

GY

FUEL

C

OM

BU

STIO

N

AC

TIVI

TIES

FUG

ITIV

E EM

ISSI

ON

S FR

OM

FU

ELS

IND

UST

RIA

L PR

OC

ESSE

S an

d PR

OD

UC

T U

SE

AG

RIC

ULT

UR

E

WA

STE

OTH

ER E

MIS

SIO

N

SOU

RC

ES

NA

TIO

NA

L TO

TAL

Inte

rnat

iona

l

Bun

kers

1990 1 052.4 1 052.4 NA 634.1 8.0 60.3 NO 1 754.8 0.2

1991 1 058.8 1 058.8 NA 544.5 7.8 49.6 NO 1 660.7 0.3

1992 968.9 968.9 NA 400.3 7.8 6.5 NO 1 383.6 0.3

1993 897.3 897.3 NA 339.1 6.9 5.8 NO 1 249.2 0.3

1994 828.2 828.2 NA 301.9 7.9 5.1 NO 1 143.1 0.3

1995 764.3 764.3 NA 278.1 8.2 3.2 NO 1 053.8 0.3

1996 782.7 782.7 NA 260.2 7.4 3.1 NO 1 053.4 0.4

1997 733.1 733.1 NA 264.2 8.0 3.1 NO 1 008.4 0.4

1998 675.6 675.6 NA 267.7 7.9 3.0 NO 954.3 0.4

1999 719.9 719.9 NA 277.2 8.4 3.0 NO 1 008.4 0.4

2000 685.9 685.9 NA 288.8 7.6 3.0 NO 985.3 0.4

2001 706.9 706.9 NA 283.3 8.6 2.9 NO 1 001.8 0.4

2002 669.9 669.9 NA 295.0 8.3 2.9 NO 976.3 0.4

2003 696.5 696.5 NA 292.6 7.5 2.9 NO 999.6 0.3

2004 691.4 691.4 NA 287.6 13.3 3.0 NO 995.3 0.4

2005 720.4 720.4 NA 302.9 7.2 2.7 NO 1 033.2 0.5

2006 760.6 760.6 NA 311.3 6.3 2.5 NO 1 080.8 0.5

2007 772.9 772.9 NA 323.2 6.8 2.7 NO 1 105.6 0.5

2008 792.6 792.6 NA 319.8 6.6 2.5 NO 1 121.5 0.5

2009 793.1 793.1 NA 259.1 6.2 2.4 NO 1 060.7 0.5

2010 865.1 865.1 NA 312.2 5.9 2.4 NO 1 185.7 0.5

2011 840.6 840.6 NA 315.4 3.9 2.3 NO 1 162.3 0.5

2012 862.3 862.3 NA 312.3 2.3 2.3 NO 1 179.2 0.5

2013 869.5 869.5 NA 329.2 2.0 2.1 NO 1 202.7 0.5

2014 809.3 809.3 NA 323.6 2.5 2.3 NO 1 137.7 0.5

2015 828.8 828.8 NA 314.3 1.8 2.3 NO 1 147.2 0.5

2016 825.9 825.9 NA 306.9 1.9 2.1 NO 1 136.8 0.6

2017 844.3 844.3 NA 329.8 1.5 2.1 NO 1 177.7 0.5

2018 843.7 843.7 NA 286.7 1.5 1.9 NO 1 133.7 0.6



Table A-7: Emission trends for Hg [kg] 1990–2018 – Submission under UNECE/LRTAP.

Hg NFR Sectors 1 1.A 1.B 2 3 5 6

ENER

GY

FUEL

C

OM

BU

STIO

N

AC

TIVI

TIES

FUG

ITIV

E EM

ISSI

ON

S FR

OM

FU

ELS

IND

UST

RIA

L PR

OC

ESSE

S an

d PR

OD

UC

T U

SE

AG

RIC

ULT

UR

E

WA

STE

OTH

ER E

MIS

SIO

N

SOU

RC

ES

NA

TIO

NA

L TO

TAL

Inte

rnat

iona

l

Bun

kers

1990 1 574.6 1 574.6 NA 534.1 1.6 54.8 NO 2 165.1 0.1

1991 1 510.3 1 510.3 NA 498.2 1.6 48.4 NO 2 058.5 0.1

1992 1 194.5 1 194.5 NA 440.9 1.6 27.8 NO 1 664.8 0.1

1993 967.5 967.5 NA 417.1 1.4 28.0 NO 1 414.1 0.1

1994 767.3 767.3 NA 403.8 1.6 27.8 NO 1 200.4 0.1

1995 720.9 720.9 NA 471.8 1.6 28.0 NO 1 222.3 0.1

1996 716.2 716.2 NA 436.4 1.5 26.7 NO 1 180.8 0.1

1997 687.1 687.1 NA 439.0 1.6 24.9 NO 1 152.6 0.1

1998 604.7 604.7 NA 338.9 1.6 22.8 NO 968.0 0.1

1999 647.1 647.1 NA 281.2 1.6 20.8 NO 950.7 0.1

2000 643.6 643.6 NA 246.7 1.5 18.1 NO 909.9 0.1

2001 702.1 702.1 NA 250.0 1.7 18.4 NO 972.3 0.1

2002 654.7 654.7 NA 266.1 1.6 19.5 NO 941.9 0.1

2003 694.0 694.0 NA 266.5 1.5 20.0 NO 982.0 0.1

2004 647.9 647.9 NA 276.8 2.5 20.6 NO 947.7 0.1

2005 657.3 656.3 1.0 310.0 1.4 21.7 NO 990.3 0.2

2006 684.2 682.9 1.3 316.1 1.2 22.3 NO 1 023.9 0.2

2007 670.5 669.4 1.1 334.7 1.3 23.7 NO 1 030.2 0.2

2008 683.4 682.7 0.7 334.3 1.3 24.7 NO 1 043.7 0.2

2009 646.5 645.8 0.7 251.2 1.2 26.4 NO 925.2 0.2

2010 677.7 677.0 0.6 323.5 1.1 27.6 NO 1 029.8 0.2

2011 662.2 661.7 0.5 333.3 0.8 28.4 NO 1 024.6 0.2

2012 677.0 676.7 0.3 329.1 0.5 30.6 NO 1 037.2 0.2

2013 707.3 707.1 0.1 349.3 0.4 31.6 NO 1 088.5 0.2

2014 661.4 661.2 0.2 341.6 0.5 32.4 NO 1 035.9 0.2

2015 643.3 643.2 0.0 331.8 0.4 35.5 NO 1 011.0 0.2

2016 593.8 593.8 0.0 322.9 0.4 35.6 NO 952.7 0.2

2017 632.2 632.2 0.0 361.2 0.3 37.9 NO 1 031.7 0.2

2018 617.5 617.4 0.1 302.0 0.3 39.2 NO 959.1 0.2



Table A-8: Emission trends for Pb [kg] 1990–2018 – Submission under UNECE/LRTAP.

Pb NFR Sectors 1 1.A 1.B 2 3 5 6

ENER

GY

FUEL

C

OM

BU

STIO

N

AC

TIVI

TIES

FUG

ITIV

E EM

ISSI

ON

S FR

OM

FU

ELS

IND

UST

RIA

L PR

OC

ESSE

S an

d PR

OD

UC

T U

SE

AG

RIC

ULT

UR

E

WA

STE

OTH

ER E

MIS

SIO

N

SOU

RC

ES

NA

TIO

NA

L TO

TAL

Inte

rnat

iona

l

Bun

kers

1990 193 979.7 193 979.7 NA 37 414.8 3.8 1 016.3 NO 232 414.6 0.2

1991 163 396.2 163 396.2 NA 32 145.5 3.7 778.1 NO 196 323.5 0.3

1992 116 425.7 116 425.7 NA 22 903.9 3.7 488.8 NO 139 822.2 0.3

1993 79 341.5 79 341.5 NA 19 339.5 3.6 381.6 NO 99 066.2 0.3

1994 51 655.4 51 655.4 NA 16 696.5 3.7 266.3 NO 68 621.9 0.3

1995 11 448.8 11 448.8 NA 8 893.0 3.7 9.8 NO 20 355.3 0.3

1996 11 364.3 11 364.3 NA 8 540.5 3.5 9.7 NO 19 918.1 0.4

1997 10 365.3 10 365.3 NA 8 459.0 3.5 9.7 NO 18 837.5 0.4

1998 9 647.6 9 647.6 NA 8 009.1 3.4 9.6 NO 17 669.7 0.4

1999 9 459.5 9 459.5 NA 8 451.5 3.5 9.6 NO 17 924.1 0.4

2000 8 973.7 8 973.7 NA 8 179.6 3.4 9.5 NO 17 166.2 0.4

2001 9 322.2 9 322.2 NA 7 422.8 3.4 9.5 NO 16 757.9 0.4

2002 9 282.5 9 282.5 NA 8 314.9 3.4 9.5 NO 17 610.2 0.4

2003 9 672.6 9 672.6 NA 8 112.9 3.2 9.5 NO 17 798.2 0.3

2004 9 848.6 9 848.6 NA 7 913.3 4.0 9.5 NO 17 775.4 0.4

2005 9 670.0 9 670.0 NA 8 695.7 3.3 9.4 NO 18 378.3 0.5

2006 10 102.2 10 102.2 NA 9 078.0 3.2 7.8 NO 19 191.2 0.5

2007 10 440.8 10 440.8 NA 9 490.9 3.3 6.6 NO 19 941.6 0.5

2008 10 537.1 10 537.1 NA 9 419.9 3.1 5.3 NO 19 965.4 0.5

2009 10 346.8 10 346.8 NA 7 225.2 3.0 3.9 NO 17 578.8 0.5

2010 11 261.8 11 261.8 NA 8 852.3 2.9 2.7 NO 20 119.7 0.5

2011 11 159.8 11 159.8 NA 9 239.3 2.7 2.6 NO 20 404.4 0.5

2012 11 361.5 11 361.5 NA 8 963.7 2.5 2.6 NO 20 330.4 0.5

2013 11 513.0 11 513.0 NA 9 595.1 2.5 2.5 NO 21 113.0 0.5

2014 10 922.5 10 922.5 NA 9 247.4 2.6 2.5 NO 20 175.0 0.5

2015 11 167.2 11 167.2 NA 8 401.7 2.5 2.5 NO 19 573.9 0.5

2016 11 309.1 11 309.1 NA 8 618.1 2.5 2.4 NO 19 932.2 0.6

2017 11 462.5 11 462.5 NA 9 067.7 2.5 2.4 NO 20 535.2 0.5

2018 11 474.1 11 474.1 NA 7 778.4 2.5 2.3 NO 19 257.2 0.6



Table A-9: Emission trends for PAH [kg] 1990–2018 – Submission under UNECE/LRTAP.

PAH NFR Sectors 1 1.A 1.B 2 3 5 6

ENER

GY

FUEL

C

OM

BU

STIO

N

AC

TIVI

TIES

FUG

ITIV

E EM

ISSI

ON

S FR

OM

FU

ELS

IND

UST

RIA

L PR

OC

ESSE

S an

d PR

OD

UC

T U

SE

AG

RIC

ULT

UR

E

WA

STE

OTH

ER E

MIS

SIO

N

SOU

RC

ES

NA

TIO

NA

L TO

TAL

Inte

rnat

iona

l B

unke

rs

1990 11 809.3 11 809.3 NA 7 138.3 81.8 0.2 NO 19 029.7 NE

1991 12 749.7 12 749.7 NA 6 936.3 80.3 0.2 NO 19 766.6 NE

1992 11 417.0 11 417.0 NA 3 087.5 80.9 0.0 NO 14 585.4 NE

1993 11 157.7 11 157.7 NA 519.2 75.8 0.0 NO 11 752.8 NE

1994 10 061.9 10 061.9 NA 405.2 78.8 0.0 NO 10 545.9 NE

1995 10 418.7 10 418.7 NA 291.9 77.7 0.0 NO 10 788.3 NE

1996 10 960.9 10 960.9 NA 254.1 75.0 0.0 NO 11 290.0 NE

1997 9 834.8 9 834.8 NA 225.3 76.5 0.0 NO 10 136.8 NE

1998 9 205.8 9 205.8 NA 199.1 75.1 0.0 NO 9 480.0 NE

1999 8 969.6 8 969.6 NA 201.4 75.9 0.0 NO 9 246.9 NE

2000 8 288.6 8 288.6 NA 183.1 69.6 0.0 NO 8 541.3 NE

2001 8 419.3 8 419.3 NA 185.0 73.5 0.0 NO 8 677.8 NE

2002 7 554.7 7 554.7 NA 194.3 70.5 0.0 NO 7 819.5 NE

2003 7 189.4 7 189.4 NA 194.5 68.0 0.0 NO 7 452.0 NE

2004 6 942.5 6 942.5 NA 200.6 90.0 0.0 NO 7 233.1 NE

2005 6 953.1 6 953.1 NA 219.6 67.0 0.0 NO 7 239.7 NE

2006 7 177.5 7 177.5 NA 223.3 64.4 0.0 NO 7 465.3 NE

2007 7 149.4 7 149.4 NA 234.0 65.0 0.0 NO 7 448.5 NE

2008 7 141.5 7 141.5 NA 232.6 62.5 0.0 NO 7 436.7 NE

2009 7 082.8 7 082.8 NA 184.6 58.6 0.0 NO 7 326.0 NE

2010 7 790.6 7 790.6 NA 225.8 57.1 0.0 NO 8 073.5 NE

2011 7 143.3 7 143.3 NA 231.6 49.4 0.0 NO 7 424.2 NE

2012 7 415.1 7 415.1 NA 229.2 43.5 0.0 NO 7 687.8 NE

2013 7 585.4 7 585.4 NA 241.8 42.0 0.0 NO 7 869.3 NE

2014 6 739.9 6 739.9 NA 237.8 44.4 0.0 NO 7 022.1 NE

2015 7 020.2 7 020.2 NA 230.5 42.4 0.0 NO 7 293.1 NE

2016 7 077.2 7 077.2 NA 225.3 42.8 0.0 NO 7 345.3 NE

2017 7 105.1 7 105.1 NA 247.8 41.7 0.0 NO 7 394.6 NE

2018 6 541.4 6 541.4 NA 213.4 41.5 0.0 NO 6 796.3 NE



Table A-10: Emission trends for Dioxin/Furan (PCDD/F) [g] 1990–2018 – Submission under UNECE/LRTAP.

DIOX NFR Sectors 1 1.A 1.B 2 3 5 6

ENER

GY

FUEL

C

OM

BU

STIO

N

AC

TIVI

TIES

FUG

ITIV

E EM

ISSI

ON

S FR

OM

FU

ELS

IND

UST

RIA

L PR

OC

ESSE

S an

d PR

OD

UC

T U

SE

AG

RIC

ULT

UR

E

WA

STE

OTH

ER E

MIS

SIO

N

SOU

RC

ES

NA

TIO

NA

L TO

TAL

Inte

rnat

iona

l

Bun

kers

1990 61.85 61.85 NA 42.85 0.18 20.29 NO 125.17 NE

1991 65.79 65.79 NA 38.96 0.18 19.88 NO 124.81 NE

1992 49.05 49.05 NA 24.63 0.18 2.68 NO 76.55 NE

1993 44.93 44.93 NA 19.14 0.18 2.38 NO 66.63 NE

1994 40.50 40.50 NA 13.41 0.18 2.26 NO 56.35 NE

1995 40.84 40.84 NA 14.37 0.18 2.27 NO 57.66 NE

1996 42.14 42.14 NA 13.31 0.18 2.26 NO 57.89 NE

1997 37.53 37.53 NA 18.19 0.18 2.27 NO 58.17 NE

1998 35.00 35.00 NA 17.49 0.18 2.28 NO 54.95 NE

1999 34.90 34.90 NA 14.26 0.18 2.29 NO 51.63 NE

2000 32.22 32.22 NA 15.71 0.18 2.31 NO 50.41 NE

2001 33.06 33.06 NA 15.13 0.18 2.31 NO 50.68 NE

2002 30.41 30.41 NA 4.73 0.18 2.34 NO 37.66 NE

2003 29.99 29.99 NA 4.40 0.17 2.36 NO 36.91 NE

2004 28.88 28.88 NA 4.64 0.22 2.37 NO 36.12 NE

2005 28.28 28.28 NA 5.29 0.15 2.04 NO 35.77 NE

2006 28.96 28.96 NA 5.97 0.15 2.03 NO 37.10 NE

2007 28.92 28.92 NA 5.24 0.15 2.54 NO 36.85 NE

2008 29.14 29.14 NA 4.72 0.13 2.48 NO 36.47 NE

2009 28.60 28.60 NA 5.11 0.13 2.47 NO 36.32 NE

2010 31.51 31.51 NA 6.47 0.13 2.89 NO 41.00 NE

2011 28.95 28.95 NA 6.34 0.09 2.80 NO 38.18 NE

2012 29.79 29.79 NA 6.30 0.07 2.87 NO 39.04 NE

2013 30.49 30.49 NA 6.66 0.06 2.52 NO 39.74 NE

2014 26.86 26.86 NA 6.82 0.07 2.90 NO 36.66 NE

2015 27.90 27.90 NA 6.82 0.06 2.92 NO 37.70 NE

2016 27.60 27.60 NA 6.83 0.06 2.75 NO 37.25 NE

2017 27.56 27.56 NA 6.78 0.06 2.78 NO 37.18 NE

2018 25.58 25.58 NA 6.40 0.05 2.37 NO 34.41 NE



Table A-11: Emission trends for HCB [kg] 1990–2018 – Submission under UNECE/LRTAP.

HCB NFR Sectors 1 1.A 1.B 2 3 5 6

ENER

GY

FUEL

CO

MB

UST

ION

A

CTI

VITI

ES

FUG

ITIV

E EM

ISSI

ON

S FR

OM

FU

ELS

IND

UST

RIA

L PR

OC

ESSE

S an

d PR

OD

UC

T U

SE

AG

RIC

ULT

UR

E

WA

STE

OTH

ER E

MIS

SIO

N

SOU

RC

ES

NA

TIO

NA

L TO

TAL

Inte

rnat

iona

l

B

unke

rs

1990 54.89 54.89 NA 20.07 10.15 0.39 NO 85.50 NE

1991 60.23 60.23 NA 15.72 10.15 0.28 NO 86.39 NE

1992 54.75 54.75 NA 13.72 7.65 0.11 NO 76.24 NE

1993 52.09 52.09 NA 11.16 7.90 0.05 NO 71.19 NE

1994 47.45 47.45 NA 4.70 5.86 0.02 NO 58.03 NE

1995 49.06 49.06 NA 3.66 5.59 0.02 NO 58.34 NE

1996 51.50 51.50 NA 3.43 3.98 0.02 NO 58.94 NE

1997 45.82 45.82 NA 5.60 4.55 0.02 NO 55.99 NE

1998 43.14 43.14 NA 5.44 3.12 0.03 NO 51.72 NE

1999 42.47 42.47 NA 3.51 3.47 0.03 NO 49.47 NE

2000 38.94 38.94 NA 3.83 0.53 0.03 NO 43.33 NE

2001 39.95 39.95 NA 3.69 0.51 0.03 NO 44.17 NE

2002 36.21 36.21 NA 3.84 0.47 0.03 NO 40.55 NE

2003 34.84 34.84 NA 3.81 0.56 0.03 NO 39.24 NE

2004 33.25 33.25 NA 3.90 0.54 0.03 NO 37.72 NE

2005 33.27 33.27 NA 4.25 0.17 0.03 NO 37.74 NE

2006 33.82 33.82 NA 4.29 0.21 0.04 NO 38.35 NE

2007 32.99 32.99 NA 4.48 0.23 0.04 NO 37.73 NE

2008 33.36 33.36 NA 4.45 0.23 0.04 NO 38.07 NE

2009 33.09 33.09 NA 4.08 0.21 0.04 NO 37.41 NE

2010 36.72 36.72 NA 5.28 0.83 0.04 NO 42.87 NE

2011 33.32 33.32 NA 5.43 0.62 0.04 NO 39.41 NE

2012 58.54 58.54 NA 5.37 0.53 0.05 NO 64.49 NE

2013 137.26 137.26 NA 5.66 0.70 0.05 NO 143.67 NE

2014 138.07 138.07 NA 5.63 0.74 0.05 NO 144.49 NE

2015 31.32 31.32 NA 5.71 0.18 0.06 NO 37.27 NE

2016 31.49 31.49 NA 5.61 0.94 0.06 NO 38.09 NE

2017 31.47 31.47 NA 6.07 1.81 0.06 NO 39.40 NE

2018 28.69 28.69 NA 5.36 1.52 0.06 NO 35.63 NE



Table A-12: Emission trends for PCB [kg] 1990–2018 – Submission under UNECE/LRTAP.

PCB NFR Sectors 1 1.A 1.B 2 3 5 6

ENER

GY

FUEL

CO

MB

UST

ION

A

CTI

VITI

ES

FUG

ITIV

E EM

ISSI

ON

S FR

OM

FU

ELS

IND

UST

RIA

L PR

OC

ESSE

S an

d PR

OD

UC

T U

SE

AG

RIC

ULT

UR

E

WA

STE

OTH

ER E

MIS

SIO

N

SOU

RC

ES

NA

TIO

NA

L TO

TAL

Inte

rnat

iona

l

B

unke

rs

1990 8.73 8.73 NA 38.50 NA 0.00 NO 47.23 NE

1991 9.95 9.95 NA 25.93 NA 0.00 NO 35.89 NE

1992 8.63 8.63 NA 20.24 NA 0.00 NO 28.87 NE

1993 8.44 8.44 NA 20.72 NA 0.00 NO 29.16 NE

1994 7.61 7.61 NA 19.30 NA 0.01 NO 26.91 NE

1995 6.95 6.95 NA 22.20 NA 0.01 NO 29.16 NE

1996 6.72 6.72 NA 19.65 NA 0.01 NO 26.37 NE

1997 7.05 7.05 NA 22.89 NA 0.01 NO 29.95 NE

1998 6.86 6.86 NA 23.34 NA 0.01 NO 30.20 NE

1999 5.95 5.95 NA 22.80 NA 0.01 NO 28.76 NE

2000 5.07 5.07 NA 25.11 NA 0.01 NO 30.18 NE

2001 4.95 4.95 NA 25.68 NA 0.01 NO 30.64 NE

2002 4.32 4.32 NA 27.14 NA 0.01 NO 31.46 NE

2003 4.32 4.32 NA 27.38 NA 0.01 NO 31.71 NE

2004 4.10 4.10 NA 28.44 NA 0.01 NO 32.54 NE

2005 3.70 3.70 NA 31.22 NA 0.01 NO 34.93 NE

2006 3.50 3.50 NA 31.74 NA 0.01 NO 35.24 NE

2007 2.80 2.80 NA 33.67 NA 0.01 NO 36.48 NE

2008 2.79 2.79 NA 33.60 NA 0.01 NO 36.40 NE

2009 2.43 2.43 NA 25.10 NA 0.01 NO 27.54 NE

2010 2.41 2.41 NA 32.13 NA 0.01 NO 34.55 NE

2011 2.04 2.04 NA 33.24 NA 0.01 NO 35.30 NE

2012 1.89 1.89 NA 32.93 NA 0.01 NO 34.83 NE

2013 1.90 1.90 NA 35.25 NA 0.01 NO 37.16 NE

2014 1.90 1.90 NA 34.73 NA 0.01 NO 36.64 NE

2015 1.98 1.98 NA 33.70 NA 0.01 NO 35.69 NE

2016 2.03 2.03 NA 32.68 NA 0.01 NO 34.72 NE

2017 2.05 2.05 NA 36.15 NA 0.01 NO 38.22 NE

2018 1.67 1.67 NA 30.40 NA 0.02 NO 32.09 NE



Table A-13: Emission trends for TSP [kt] 1990–2018 – Submission under UNECE/LRTAP.

TSP NFR Sectors 1 1.A 1.B 2 3 5 6

ENER

GY

FUEL

C

OM

BU

STIO

N

AC

TIVI

TIES

FUG

ITIV

E EM

ISSI

ON

S FR

OM

FU

ELS

IND

UST

RIA

L PR

OC

ESSE

S an

d PR

OD

UC

T U

SE

AG

RIC

ULT

UR

E

WA

STE

OTH

ER E

MIS

SIO

N

SOU

RC

ES

NA

TIO

NA

L TO

TAL

Inte

rnat

iona

l

Bun

kers

1990 28.60 27.74 0.85 19.31 4.95 0.35 NO 53.21 0.28

1995 27.35 26.69 0.65 19.35 4.99 0.37 NO 52.06 0.42

2000 25.99 25.33 0.66 19.47 4.81 0.30 NO 50.58 0.52

2001 26.42 25.73 0.68 18.72 4.82 0.30 NO 50.26 0.51

2002 25.96 25.24 0.72 18.10 4.79 0.32 NO 49.17 0.46

2003 25.91 25.17 0.73 17.77 4.79 0.35 NO 48.81 0.43

2004 25.21 24.59 0.62 18.34 4.87 0.39 NO 48.81 0.51

2005 25.22 24.61 0.61 17.72 4.82 0.37 NO 48.14 0.59

2006 25.05 24.47 0.58 16.55 4.76 0.37 NO 46.74 0.63

2007 24.40 23.87 0.53 16.07 4.76 0.45 NO 45.67 0.66

2008 23.34 22.81 0.53 17.12 4.71 0.40 NO 45.57 0.66

2009 22.11 21.73 0.38 15.92 4.72 0.39 NO 43.14 0.57

2010 22.93 22.46 0.47 15.68 4.70 0.46 NO 43.77 0.62

2011 21.75 21.26 0.48 16.13 4.66 0.48 NO 43.01 0.65

2012 21.34 20.90 0.44 15.76 4.62 0.54 NO 42.26 0.62

2013 20.82 20.36 0.45 15.69 4.60 0.51 NO 41.62 0.59

2014 18.94 18.53 0.41 16.09 4.60 0.62 NO 40.25 0.59

2015 18.99 18.55 0.45 15.53 4.58 0.71 NO 39.81 0.63

2016 18.61 18.19 0.42 15.53 4.56 0.73 NO 39.43 0.70

2017 18.44 18.01 0.44 15.96 4.55 0.73 NO 39.69 0.67

2018 17.43 17.05 0.37 15.66 4.54 0.69 NO 38.32 0.76



Table A-14: Emission trends for PM10 [kt] 1990–2018 – Submission under UNECE/LRTAP.

PM10 NFR Sectors 1 1.A 1.B 2 3 5 6

ENER

GY

FUEL

C

OM

BU

STIO

N

AC

TIVI

TIES

FUG

ITIV

E EM

ISSI

ON

S FR

OM

FU

ELS

IND

UST

RIA

L PR

OC

ESSE

S an

d PR

OD

UC

T U

SE

AG

RIC

ULT

UR

E

WA

STE

OTH

ER E

MIS

SIO

N

SOU

RC

ES

NA

TIO

NA

L TO

TAL

Inte

rnat

iona

l

Bun

kers

1990 25.22 24.82 0.40 11.16 4.24 0.28 NO 40.90 0.28

1995 24.15 23.84 0.31 10.64 4.30 0.29 NO 39.37 0.42

2000 22.80 22.49 0.31 10.59 4.17 0.26 NO 37.82 0.52

2001 23.18 22.86 0.32 10.18 4.18 0.25 NO 37.80 0.51

2002 22.73 22.39 0.34 9.57 4.17 0.27 NO 36.74 0.46

2003 22.65 22.30 0.35 9.39 4.16 0.28 NO 36.48 0.43

2004 22.02 21.73 0.29 9.61 4.25 0.30 NO 36.18 0.51

2005 22.03 21.74 0.29 9.27 4.20 0.27 NO 35.77 0.59

2006 21.82 21.54 0.27 8.56 4.14 0.27 NO 34.78 0.63

2007 21.15 20.90 0.25 8.17 4.12 0.33 NO 33.78 0.66

2008 20.12 19.88 0.25 8.71 4.08 0.31 NO 33.23 0.66

2009 19.01 18.83 0.18 8.09 4.08 0.30 NO 31.48 0.57

2010 19.68 19.46 0.22 7.98 4.06 0.35 NO 32.08 0.62

2011 18.52 18.29 0.23 8.22 4.02 0.36 NO 31.12 0.65

2012 18.12 17.91 0.21 8.01 3.99 0.39 NO 30.51 0.62

2013 17.58 17.37 0.21 7.98 3.97 0.36 NO 29.89 0.59

2014 15.82 15.62 0.19 8.14 3.96 0.43 NO 28.35 0.59

2015 15.79 15.58 0.21 7.82 3.94 0.47 NO 28.02 0.63

2016 15.40 15.20 0.20 7.84 3.91 0.47 NO 27.62 0.70

2017 15.18 14.97 0.21 8.02 3.90 0.48 NO 27.58 0.67

2018 14.21 14.03 0.18 7.86 3.90 0.44 NO 26.40 0.76



Table A-15: Emission trends for PM2.5 [kt] 1990–2018– Submission under UNECE/LRTAP.

PM2.5 NFR Sectors 1 1.A 1.B 2 3 5 6

ENER

GY

FUEL

C

OM

BU

STIO

N

AC

TIVI

TIES

FUG

ITIV

E EM

ISSI

ON

S FR

OM

FU

ELS

IND

UST

RIA

L PR

OC

ESSE

S an

d PR

OD

UC

T U

SE

AG

RIC

ULT

UR

E

WA

STE

OTH

ER E

MIS

SIO

N

SOU

RC

ES

NA

TIO

NA

L TO

TAL

Inte

rnat

iona

l

Bun

kers

1990 22.76 22.65 0.11 3.82 0.36 0.23 NO 27.17 0.28

1995 21.93 21.85 0.09 3.17 0.36 0.24 NO 25.69 0.42

2000 20.60 20.51 0.09 2.96 0.34 0.23 NO 24.12 0.52

2001 20.95 20.86 0.09 2.86 0.35 0.23 NO 24.38 0.51

2002 20.51 20.41 0.10 2.49 0.34 0.23 NO 23.56 0.46

2003 20.39 20.28 0.10 2.43 0.33 0.24 NO 23.39 0.43

2004 19.81 19.72 0.09 2.40 0.38 0.24 NO 22.83 0.51

2005 19.81 19.72 0.09 2.32 0.33 0.21 NO 22.67 0.59

2006 19.55 19.47 0.09 2.09 0.32 0.21 NO 22.17 0.63

2007 18.87 18.79 0.08 1.89 0.33 0.26 NO 21.35 0.66

2008 17.88 17.80 0.08 1.99 0.32 0.25 NO 20.44 0.66

2009 16.85 16.79 0.06 1.85 0.32 0.25 NO 19.27 0.57

2010 17.39 17.32 0.07 1.87 0.31 0.29 NO 19.87 0.62

2011 16.24 16.17 0.07 1.91 0.30 0.29 NO 18.73 0.65

2012 15.84 15.77 0.07 1.85 0.28 0.30 NO 18.27 0.62

2013 15.31 15.24 0.07 1.84 0.28 0.26 NO 17.69 0.59

2014 13.66 13.60 0.06 1.85 0.28 0.31 NO 16.11 0.59

2015 13.56 13.49 0.07 1.78 0.28 0.33 NO 15.94 0.63

2016 13.18 13.12 0.06 1.78 0.28 0.31 NO 15.56 0.70

2017 12.92 12.86 0.07 1.78 0.28 0.32 NO 15.30 0.67

2018 11.99 11.93 0.06 1.72 0.27 0.28 NO 14.26 0.76



12.2 National emission total for SO2, NOx, NMVOC and NH3 calculated on the basis of fuels used

In the following tables Austria’s emissions 1990–2018 are listed according to Directive (EU) 2016/2284 (NEC Directive). Austria uses the national emission totals calculated on the basis of fuel used (thus excluding emissions from fuel exports in the vehicle tank) for assessing compli-ance with the 2010 emission ceilings under the NEC Directive. Emissions are reported on the basis of fuel used (without ‘fuel export’).

The complete tables of the NFR Format are submitted separately in digital form only (excel files).

Table A-16: Emission trends 1990–2018 on the basis of fuel used.

SO2 [kt]

NOx [kt]

NMVOC [kt]

NH3 [kt]

1990 72.90 199.91 329.26 61.68

1991 69.66 201.55 317.68 62.40

1992 53.15 193.58 298.52 60.94

1993 51.64 185.07 280.44 61.96

1994 46.14 180.89 260.05 61.95

1995 45.85 180.09 244.98 63.06

1996 43.18 180.48 236.83 62.53

1997 39.97 180.78 223.70 62.86

1998 34.97 179.10 213.05 63.10

1999 33.27 179.21 203.49 62.04

2000 31.04 178.87 179.43 60.71

2001 31.81 181.89 172.54 60.64

2002 30.70 181.62 165.43 59.63

2003 30.43 186.13 161.23 59.52

2004 26.54 186.03 148.32 59.35

2005 25.90 189.41 152.63 59.24

2006 26.75 190.95 155.93 59.74

2007 23.41 187.28 151.77 61.05

2008 20.30 180.60 146.55 60.80

2009 14.76 168.03 133.31 62.22

2010 16.00 168.18 133.44 62.19

2011 15.20 166.85 128.40 61.72

2012 14.83 162.72 126.10 62.04

2013 14.40 159.61 120.34 62.16

2014 14.51 155.79 113.64 62.94

2015 13.95 153.92 110.48 63.72

2016 13.28 150.00 108.85 64.52

2017 12.81 143.42 109.94 65.39

2018 11.73 135.74 106.55 64.38



Table A-17: Emission trends for SOx [kt] 1990–2018 on the basis of fuel used.

SOx NFR Sectors 1 1.A 1.B 2 3 5 6

ENER

GY

FUEL

C

OM

BU

STIO

N

AC

TIVI

TIES

FUG

ITIV

E EM

ISSI

ON

S FR

OM

FU

ELS

IND

UST

RIA

L PR

OC

ESSE

S an

d PR

OD

UC

T U

SE

AG

RIC

ULT

UR

E

WA

STE

OTH

ER

NA

TIO

NA

L TO

TAL

Inte

rnat

iona

l B

unke

rs

kt

1990 70.89 68.89 2.00 1.93 0.01 0.07 NO 72.90 0.26

1991 67.99 66.69 1.30 1.61 0.00 0.06 NO 69.66 0.29

1992 51.74 49.74 2.00 1.36 0.00 0.04 NO 53.15 0.31

1993 50.48 48.38 2.10 1.11 0.00 0.04 NO 51.64 0.33

1994 44.97 43.69 1.28 1.12 0.00 0.05 NO 46.14 0.34

1995 44.73 43.20 1.53 1.07 0.01 0.05 NO 45.85 0.38

1996 42.14 40.94 1.20 0.99 0.00 0.05 NO 43.18 0.43

1997 38.95 38.88 0.07 0.96 0.00 0.05 NO 39.97 0.44

1998 34.04 34.00 0.04 0.87 0.00 0.06 NO 34.97 0.46

1999 32.40 32.35 0.04 0.81 0.01 0.06 NO 33.27 0.45

2000 30.20 30.16 0.04 0.78 0.00 0.06 NO 31.04 0.48

2001 31.04 30.99 0.05 0.71 0.01 0.06 NO 31.81 0.47

2002 29.93 29.89 0.04 0.71 0.01 0.06 NO 30.70 0.43

2003 29.66 29.61 0.05 0.71 0.00 0.06 NO 30.43 0.40

2004 25.75 25.71 0.04 0.72 0.01 0.06 NO 26.54 0.47

2005 25.11 25.07 0.04 0.72 0.00 0.06 NO 25.90 0.55

2006 25.97 25.92 0.05 0.73 0.00 0.05 NO 26.75 0.58

2007 22.62 22.56 0.05 0.75 0.00 0.04 NO 23.41 0.61

2008 19.48 19.44 0.04 0.78 0.00 0.03 NO 20.30 0.61

2009 14.04 13.98 0.06 0.70 0.00 0.02 NO 14.76 0.53

2010 15.28 15.23 0.05 0.70 0.00 0.01 NO 16.00 0.57

2011 14.50 14.46 0.05 0.68 0.00 0.01 NO 15.20 0.60

2012 14.17 14.12 0.05 0.65 0.00 0.01 NO 14.83 0.57

2013 13.80 13.76 0.04 0.59 0.00 0.01 NO 14.40 0.54

2014 13.95 13.91 0.04 0.55 0.00 0.01 NO 14.51 0.54

2015 13.37 13.33 0.04 0.57 0.00 0.01 NO 13.95 0.58

2016 12.70 12.68 0.02 0.57 0.00 0.01 NO 13.28 0.54

2017 12.22 12.19 0.04 0.57 0.00 0.01 NO 12.81 0.52

2018 11.15 11.12 0.02 0.57 0.00 0.01 NO 11.73 0.59



Table A-18: Emission trends for NOx [kt] 1990–2018 on the basis of fuel used.

NOx NFR Sectors 1 1.A 1.B 2 4 6 7

ENER

GY

FUEL

C

OM

BU

STIO

N

AC

TIVI

TIES

FUG

ITIV

E EM

ISSI

ON

S FR

OM

FU

ELS

IND

UST

RIA

L PR

OC

ESSE

S an

d PR

OD

UC

T U

SE

AG

RIC

ULT

UR

E

WA

STE

OTH

ER

NA

TIO

NA

L TO

TAL

Inte

rnat

iona

l B

unke

rs

kt

1990 183.48 183.48 IE 4.27 12.05 0.10 NO 199.91 2.44

1991 185.54 185.54 IE 3.93 11.99 0.09 NO 201.55 2.76

1992 177.78 177.78 IE 4.02 11.73 0.06 NO 193.58 3.00

1993 171.99 171.99 IE 1.46 11.57 0.05 NO 185.07 3.18

1994 168.03 168.03 IE 1.38 11.43 0.05 NO 180.89 3.31

1995 167.53 167.53 IE 0.90 11.61 0.05 NO 180.09 3.73

1996 168.07 168.07 IE 0.87 11.50 0.05 NO 180.48 4.14

1997 168.30 168.30 IE 0.86 11.57 0.05 NO 180.78 4.29

1998 166.60 166.60 IE 0.83 11.62 0.05 NO 179.10 4.43

1999 167.07 167.07 IE 0.82 11.27 0.05 NO 179.21 4.33

2000 166.91 166.91 IE 0.83 11.08 0.05 NO 178.87 6.44

2001 170.01 170.01 IE 0.78 11.05 0.05 NO 181.89 6.32

2002 169.72 169.72 IE 0.79 11.07 0.05 NO 181.62 5.67

2003 174.68 174.68 IE 0.81 10.59 0.05 NO 186.13 5.21

2004 175.23 175.23 IE 0.69 10.06 0.05 NO 186.03 6.09

2005 178.54 178.54 IE 0.70 10.12 0.05 NO 189.41 6.99

2006 180.16 180.16 IE 0.58 10.16 0.04 NO 190.95 7.54

2007 176.45 176.45 IE 0.48 10.31 0.04 NO 187.28 7.99

2008 169.11 169.11 IE 0.56 10.90 0.03 NO 180.60 7.90

2009 156.91 156.91 IE 0.41 10.69 0.02 NO 168.03 6.86

2010 157.84 157.84 IE 0.55 9.78 0.02 NO 168.18 7.60

2011 156.03 156.03 IE 0.52 10.28 0.02 NO 166.85 7.98

2012 151.76 151.76 IE 0.55 10.40 0.02 NO 162.72 7.68

2013 148.85 148.85 IE 0.45 10.29 0.02 NO 159.61 7.46

2014 144.72 144.72 IE 0.46 10.60 0.02 NO 155.79 7.49

2015 142.40 142.40 IE 0.52 10.99 0.02 NO 153.92 8.18

2016 138.29 138.29 IE 0.52 11.17 0.02 NO 150.00 10.28

2017 131.94 131.94 IE 0.47 10.99 0.02 NO 143.42 10.06

2018 124.56 124.56 IE 0.41 10.75 0.02 NO 135.74 11.54



Table A-19: Emission trends for NMVOC [kt] 1990–2018 on the basis of fuel used.

NMVOC NFR Sectors 1 1.A 1.B 2 4 6 7

ENER

GY

FUEL

C

OM

BU

STIO

N

AC

TIVI

TIES

FUG

ITIV

E EM

ISSI

ON

S FR

OM

FU

ELS

IND

UST

RIA

L PR

OC

ESSE

S

AG

RIC

ULT

UR

E

WA

STE

OTH

ER

NA

TIO

NA

L TO

TAL

Inte

rnat

iona

l B

unke

rs

kt

1990 158.38 142.89 15.49 118.54 52.19 0.16 NO 329.26 0.18

1991 154.30 139.18 15.12 112.01 51.21 0.16 NO 317.68 0.20

1992 144.59 129.40 15.19 105.25 48.54 0.15 NO 298.52 0.22

1993 134.49 119.83 14.65 98.55 47.26 0.15 NO 280.44 0.24

1994 121.13 110.01 11.12 91.99 46.79 0.14 NO 260.05 0.25

1995 113.32 103.83 9.49 85.28 46.25 0.14 NO 244.98 0.29

1996 107.88 99.41 8.46 83.72 45.10 0.13 NO 236.83 0.34

1997 96.87 88.91 7.95 82.37 44.33 0.13 NO 223.70 0.37

1998 87.88 81.44 6.43 81.06 43.99 0.13 NO 213.05 0.40

1999 81.77 76.10 5.67 78.32 43.28 0.12 NO 203.49 0.39

2000 74.89 69.20 5.69 62.15 42.27 0.12 NO 179.43 0.42

2001 70.64 66.81 3.84 59.96 41.82 0.11 NO 172.54 0.41

2002 65.27 61.24 4.03 59.11 40.94 0.11 NO 165.43 0.37

2003 62.15 58.19 3.96 58.53 40.44 0.11 NO 161.23 0.34

2004 58.25 54.68 3.57 49.80 40.16 0.11 NO 148.32 0.40

2005 55.70 52.35 3.34 57.32 39.50 0.11 NO 152.63 0.47

2006 53.37 50.01 3.36 63.26 39.19 0.10 NO 155.93 0.50

2007 50.66 47.68 2.98 61.94 39.07 0.10 NO 151.77 0.53

2008 48.96 46.20 2.75 58.71 38.79 0.10 NO 146.55 0.52

2009 46.35 43.76 2.59 47.89 38.98 0.09 NO 133.31 0.45

2010 48.07 45.62 2.45 46.70 38.58 0.09 NO 133.44 0.49

2011 44.37 41.96 2.41 46.03 37.92 0.08 NO 128.40 0.51

2012 44.28 41.88 2.40 44.13 37.61 0.08 NO 126.10 0.49

2013 43.82 41.52 2.30 38.87 37.58 0.07 NO 120.34 0.46

2014 39.13 36.71 2.42 36.81 37.63 0.07 NO 113.64 0.46

2015 39.62 37.30 2.32 33.37 37.43 0.06 NO 110.48 0.50

2016 39.04 36.77 2.27 32.33 37.42 0.06 NO 108.85 0.23

2017 38.61 36.32 2.29 33.96 37.31 0.06 NO 109.94 0.20

2018 35.89 33.72 2.17 33.63 36.97 0.06 NO 106.55 0.22



Table A-20: Emission trends for NH3 [kt] 1990–2018 on the basis of fuel used.

NH3 NFR Sectors 1 1.A 1.B 2 4 6 7

ENER

GY

FUEL

C

OM

BU

STIO

N

AC

TIVI

TIES

FUG

ITIV

E EM

ISSI

ON

S FR

OM

FU

ELS

IND

UST

RIA

L PR

OC

ESSE

S

AG

RIC

ULT

UR

E

WA

STE

OTH

ER

NA

TIO

NA

L TO

TAL

Inte

rnat

iona

l B

unke

rs

kt

1990 1.911 1.911 IE 0.339 59.063 0.367 NO 61.680 0.002

1991 2.258 2.258 IE 0.577 59.181 0.382 NO 62.398 0.002

1992 2.483 2.483 IE 0.438 57.588 0.434 NO 60.943 0.002

1993 2.786 2.786 IE 0.287 58.370 0.515 NO 61.958 0.002

1994 2.976 2.976 IE 0.236 58.121 0.622 NO 61.955 0.002

1995 3.181 3.181 IE 0.165 59.076 0.642 NO 63.064 0.003

1996 3.480 3.480 IE 0.163 58.223 0.668 NO 62.534 0.003

1997 3.600 3.600 IE 0.162 58.435 0.666 NO 62.864 0.003

1998 3.754 3.754 IE 0.168 58.476 0.697 NO 63.096 0.003

1999 3.930 3.930 IE 0.186 57.153 0.767 NO 62.036 0.003

2000 3.880 3.880 IE 0.167 55.838 0.822 NO 60.707 0.003

2001 3.899 3.899 IE 0.146 55.670 0.922 NO 60.636 0.003

2002 3.694 3.694 IE 0.128 54.794 1.018 NO 59.633 0.003

2003 3.607 3.607 IE 0.141 54.673 1.099 NO 59.520 0.003

2004 3.449 3.449 IE 0.122 54.429 1.346 NO 59.347 0.003

2005 3.384 3.379 0.005 0.127 54.292 1.444 NO 59.246 0.004

2006 3.349 3.342 0.006 0.136 54.789 1.470 NO 59.742 0.004

2007 3.249 3.244 0.005 0.138 56.149 1.515 NO 61.050 0.004

2008 3.079 3.075 0.003 0.140 56.051 1.535 NO 60.805 0.004

2009 2.876 2.872 0.003 0.148 57.623 1.571 NO 62.219 0.004

2010 2.941 2.938 0.003 0.153 57.538 1.565 NO 62.196 0.004

2011 2.727 2.725 0.002 0.160 57.273 1.563 NO 61.723 0.004

2012 2.634 2.632 0.001 0.153 57.672 1.584 NO 62.043 0.004

2013 2.512 2.511 0.001 0.155 57.961 1.532 NO 62.159 0.004

2014 2.321 2.320 0.001 0.148 58.896 1.579 NO 62.944 0.004

2015 2.347 2.347 0.000 0.140 59.621 1.611 NO 63.719 0.004

2016 2.276 2.276 0.000 0.146 60.505 1.598 NO 64.525 0.004

2017 2.318 2.317 0.000 0.167 61.300 1.602 NO 65.386 0.004

2018 2.282 2.281 0.001 0.135 60.358 1.601 NO 64.376 0.005



12.3 Information on PM emission factors (include/exclude the condensable component)

Table A-21: PM emission factors per source category and information on condensable component.

NFR Source/sector name PM emissions: the con-densable component is EF reference and

comments included excluded

1.A.1.a Public electricity and heat production Partially (large plants)

Small bio-mass plants w/o second-ary filtering (ESP, fabric)

Large plants: Continu-ous Stack measure-ments. Small biomass plants: national study based on flue gas con-centrations of funded plants.

1.A.1.b Petroleum refining X Continuous Stack measurements.

1.A.1.c Manufacture of solid fuels and other energy industries X

Charcoal production: unknown

Natural gas only. Na-tional study.

1.A.2.a Stationary combustion in manufactur-ing industries and construction: Iron and steel

X National studies,

based on stack meas-urements.

1.A.2.b Stationary combustion in manufactur-ing industries and construction: Non-ferrous metals

X National studies,


1.A.2.c Stationary combustion in manufactur-ing industries and construction: Chemicals

X National studies,


1.A.2.d Stationary combustion in manufactur-ing industries and construction: Pulp, Paper and Print

X National studies,


1.A.2.e Stationary combustion in manufactur-ing industries and construction: Food processing, beverages and tobacco

X National studies,


1.A.2.f Stationary combustion in manufactur-ing industries and construction: Non-metallic minerals

X National studies,


1.A.2.g.vii Mobile Combustion in manufacturing industries and construction: (please specify in the IIR)

X TU GRAZ

(Graz University of Technology)

1.A.2.g.viii Stationary combustion in manufactur-ing industries and construction: Other (please specify in the IIR)

X National studies,


1.A.3.a.i(i) International aviation LTO (civil) No information available.

KALIVODA & KUDRNA 2002 1.A.3.a.ii(i) Domestic aviation LTO (civil)

1.A.3.b.i Road transport: Passenger cars X TU GRAZ (Graz University of Technology)

1.A.3.b.ii Road transport: Light duty vehicles X

1.A.3.b.iii Road transport: Heavy duty vehicles and buses X

1.A.3.b.iv Road transport: Mopeds & motorcyc-les X

1.A.3.b.v Road transport: Gasoline evaporation NA

1.A.3.b.vi Road transport: Automobile tyre and brake wear

No information in the EMEP/EEA GB 2016 EMEP/EEA GB 2016

1.A.3.b.vii Road transport: Automobile road abrasion






1.A.3.c Railways No information in the EMEP/EEA GB 2016 EMEP/EEA GB 2016

1.A.3.d.i(ii) International inland waterways No information in the EMEP/EEA GB 2016

EMEP/EEA GB 2016 1.A.3.d.ii National navigation (shipping) EMEP/EEA GB 2016 1.A.3.e.i Pipeline transport X Natural gas only. 1.A.3.e.ii Other (please specify in the IIR) NO

1.A.4.a.i Commercial/institutional: Stationary X X

In general, there is a lack of information. Only a few emission factors include the condensable fraction, see Table NFR 1.A.4. PM emission factors for the year 2017. (EMEP/EEA Guide-book 2016), (WINIWARTER et al. 2001), (WINIWARTER et al. 2007), (FOEN 2015), German Envi-ronment Agency (2008).

1.A.4.a.ii Commercial/institutional: Mobile IE

1.A.4.b.i Residential: Stationary X X


1.A.4.b.ii Residential: Household and garden-ing (mobile) X

TU GRAZ (Graz University of Technology)





1.A.4.c.i Agriculture/Forestry/Fishing: Statio-nary X X


1.A.4.c.ii Agriculture/Forestry/Fishing: Off-road vehicles and other machinery X


1.A.4.c.iii Agriculture/Forestry/Fishing: National fishing NO

1.A.5.a Other stationary (including military) NO

1.A.5.b Other, Mobile (including military, land based and recreational boats) X


1.B.1.a Fugitive emission from solid fuels: Coal mining and handling


1.B.1.b Fugitive emission from solid fuels: Solid fuel transformation IE

1.B.1.c Other fugitive emissions from solid fuels NO

1.B.2.a.i Fugitive emissions oil: Exploration, production, transport NA

1.B.2.a.iv Fugitive emissions oil: Refining / storage IE

1.B.2.a.v Distribution of oil products NA

1.B.2.b

Fugitive emissions from natural gas (exploration, production, processing, transmission, storage, distribution and other)

NA

1.B.2.c Venting and flaring (oil, gas, com-bined oil and gas) NA

1.B.2.d Other fugitive emissions from energy production NE

2.A.1 Cement production X MAUSCHITZ 2011

2.A.2 Lime production X (diffuse) WINIWARTER et al. 2007

2.A.3 Glass production IE

2.A.5.a Quarrying and mining of minerals other than coal NA (diffuse) WINIWARTER

et al. 2007

2.A.5.b Construction and demolition NA (diffuse) WINIWARTER et al. 2007

2.A.5.c Storage, handling and transport of mineral products NO

2.A.6 Other mineral products (please specify in the IIR) NO




comments included excluded 2.B.1 Ammonia production NA 2.B.2 Nitric acid production NA 2.B.3 Adipic acid production NO 2.B.5 Carbide production NE 2.B.6 Titanium dioxide production NO 2.B.7 Soda ash production NO

2.B.10.a Chemical industry: Other (please specify in the IIR) NA (diffuse) WINIWARTER

et al. 2007

2.B.10.b Storage, handling and transport of chemical products (please specify in the IIR)

NO

2.C.1 Iron and steel production No information available

diffuse emissions + abatment technologies installed, directly re-ported by the operator

2.C.2 Ferroalloys production X EMEP/EEA GB 2016 2.C.3 Aluminium production X EMEP/EEA GB 2016 2.C.4 Magnesium production NO 2.C.5 Lead production X EMEP/EEA GB 2016 2.C.6 Zinc production NO 2.C.7.a Copper production X EMEP/EEA GB 2016 2.C.7.b Nickel production NO

2.C.7.c Other metal production (please specify in the IIR) NE

2.C.7.d "Storage, handling and transport of metal products NO

2.D.3.a Domestic solvent use including fun-gicides

NA

2.D.3.b Road paving with asphalt NA 2.D.3.c Asphalt roofing NA 2.D.3.d Coating applications NA 2.D.3.e Degreasing NA 2.D.3.f Dry cleaning NA 2.D.3.g Chemical products NA 2.D.3.h Printing NA

2.D.3.i Other solvent use (please specify in the IIR) NA

2.G Other product use (please specify in the IIR)


2.H.1 Pulp and paper industry NA

2.H.2 Food and beverages industry NA (diffuse) WINIWARTER et al. 2007

2.H.3 Other industrial processes (please specify in the IIR)

NO

2.I Wood processing NA (diffuse) WINIWARTER et al. 2007

2.J Production of POPs NO

2.K "Consumption of POPs and heavy metals (e.g. electrical and scientific equipment)"

NO

2.L

Other production, consumption, stor-age, transportation or handling of bulk products (please specify in the IIR)

NO





3.B.1.a Manure management – Dairy cattle No information available LÜKEWILLE et al. 2001 WINIWARTER et al. 2007

3.B.1.b Manure management – Non-dairy cattle No information available LÜKEWILLE et al. 2001

WINIWARTER et al. 2007

3.B.2 Manure management – Sheep No information available LÜKEWILLE et al. 2001 WINIWARTER et al. 2007

3.B.3 Manure management – Swine No information available LÜKEWILLE et al. 2001 WINIWARTER et al. 2007

3.B.4.a Manure management – Buffalo NO

3.B.4.d Manure management – Goats No information available LÜKEWILLE et al. 2001 WINIWARTER et al. 2007

3.B.4.e Manure management – Horses No information available LÜKEWILLE et al. 2001 WINIWARTER et al. 2007

3.B.4.f Manure management – Mules and asses IE

3.B.4.g.i Manure mangement – Laying hens No information available LÜKEWILLE et al. 2001 WINIWARTER et al. 2007

3.B.4.g.ii Manure mangement – Broilers No information available LÜKEWILLE et al. 2001 WINIWARTER et al. 2007

3.B.4.g.iii Manure mangement – Turkeys No information available LÜKEWILLE et al. 2001 WINIWARTER et al. 2007

3.B.4.g.iv Manure management – Other poultry No information available LÜKEWILLE et al. 2001 WINIWARTER et al. 2007

3.B.4.h Manure management – Other ani-mals (please specify in IIR) No information available LÜKEWILLE et al. 2001

WINIWARTER et al. 2007

3.D.a.1 Inorganic N-fertilizers (includes also urea application) NA

3.D.a.2.a Animal manure applied to soils NA 3.D.a.2.b Sewage sludge applied to soils NA

3.D.a.2.c "Other organic fertilisers applied to soils (including compost)" NA

3.D.a.3 Urine and dung deposited by grazing animals NA

3.D.a.4 Crop residues applied to soils NA

3.D.b Indirect emissions from managed soils NO

3.D.c Farm-level agricultural operations in-cluding storage, handling and transport of agricultural products

X EMEP/EEA GB 2019

3.D.d Off-farm storage, handling and transport of bulk agricultural products NA (diffuse) WINIWARTER

et al. 2007 3.D.e Cultivated crops NA 3.D.f Use of pesticides NA

3.F Field burning of agricultural residues No information in the EMEP/EEA GB 2019 EMEP/EEA GB 2019

3.I Agriculture other (please specify in the IIR)

NO

5.A Biological treatment of waste – Solid waste disposal on land NA (diffuse) WINIWARTER

et al. 2007

5.B.1 Biological treatment of waste – Com-posting

NA

5.B.2 Biological treatment of waste - An-aerobic digestion at biogas facilities

NA

5.C.1.a Municipal waste incineration NO




comments included excluded 5.C.1.b.i Industrial waste incineration No information available National studies 5.C.1.b.ii Hazardous waste incineration NO 5.C.1.b.iii Clinical waste incineration No information available National studies 5.C.1.b.iv Sewage sludge incineration NO 5.C.1.b.v Cremation No information available National studies

5.C.1.b.vi Other waste incineration (please specify in the IIR) NO

5.C.2 Open burning of waste NO 5.D.1 Domestic wastewater handling NA 5.D.2 Industrial wastewater handling NA 5.D.3 Other wastewater handling NO

5.E Other waste (please specify in IIR) No information in the EMEP/EEA GB 2019 EMEP/EEA GB 2019

6.A Other (included in national total for entire territory) (please specify in IIR) NO

NA: as emissions occur at ambient temperature level, it is unlikely that substantial quantities of condensable particulate material are included

The Informative Inventory Report (IIR) 2020 presents a comprehensive and

detailed description of emission trends and the methodologies applied in

the Austrian Air Emission Inventory for the air pollutants

• sulphur dioxide (SO2), nitrogen oxides (NOx), non-methane volatile

organic compounds (NMVOCs), ammonia (NH3)

• carbon monoxide (CO) and

• particulate matter (TSP, PM10, PM2.5)

as well as the air pollutant groups such as

• heavy metals: cadmium (Cd), mercury (Hg), lead (Pb) and

• persistent organic pollutants (POPs): polycyclic aromatic hydrocarbons

(PAHs), dioxins and furans (PCDD/Fs), hexachlorobenzene (HCB) as well

as polychlorinated biphenyls (PCB).

With the IIR 2020, Austria complies with its reporting obligations under

the UNECE Convention on Long-range Transboundary Air Pollution (LRTAP)

and Directive (EU) 2016/2284 on the reduction of national emissions of

certain atmospheric pollutants.

ISBN 978-3-99004-543-5

Umweltbundesamt GmbH

Spittelauer Lände 5

1090 Vienna/Austria

Tel.: +43-(0)1-313 04

Fax: +43-(0)1-313 04/5400

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